The modern healthcare environment will require ambidextrous experts in healthcare and AI.
As the artificial intelligence (AI) market grows to over$400 billion by 2027, the demand for professionals with expertise in machine learning is increasing as AI technology rapidly evolves. Within the healthcare sector, a deep knowledge of the clinical sciences and healthcare skills will no longer be enough.
Moving ahead, healthcare corporations and academia must empower ambidextrous healthcare professionals (HCPs) with expertise in both machine learning and health science to stay innovative and competitive.
What to do ?
Develop ambidextrous skills in ongoing study and research
Large healthcare companies are exploring ways to integrate AI within their businesses to drive greater efficiencies across different R&D and commercial processes and workflows. With a shift towards corporations placing outsized value on an ambidextrous skillset, HCP graduates are dedicating more focus on AI in their study and research.
Empower ambidextrous professionals to lead interdisciplinary healthcare teams
Interdisciplinary teams that empower ambidextrous AI and healthcare professionals as leaders and project owners will realize their full potential. Their leadership can help fill the gaps in knowledge and communication between team members and drive significant efficiencies.
For HCPs, their lack of technical expertise may lead to an overestimation of AI capabilities, causing a mismatch between expectations and technical realities. For machine learning experts, insufficient knowledge of healthcare can be a barrier to identifying the right problems to solve with AI, resulting in misdirected initiatives and misallocated resources.
Find and cultivate ambidextrous talent in corporate and academic environments
Identifying ambidextrous expertise in health medicine and AI is not easy. Healthcare professionals are specialized experts that take years to train. Few universities have programs that offer training in AI. This is a challenge that the life sciences industry and academia can solve together.
Ambidextrous professionals will drive AI innovation in healthcare
With the right ambidextrous people in the right roles, corporations can further innovation in AI and healthcare. Companies must place a higher emphasis on recruiting and developing ambidextrous experts. The ability to empower and retain such experts and leaders will not only alter the course of their business, but also increase their relevance as AI rapidly transforms our modern economy.
Here the full Article of the MedCity News: AI Disruption is Coming. Are Healthcare Professionals Ready?
Flexible printed circuit boards can be considered the gymnasts of electronic components. Unlike their rigid counterparts, they possess a remarkable ability to bend and adapt to different shapes, enabling more versatile designs in electronic devices. These boards are made from electrically conductive materials, allowing seamless connections between various electronic components. The flexibility of these PCBs opens the door to a new era of design possibilities.
In essence, flexible PCBs offer a dynamic and adaptable foundation for the intricate electronic systems that power our modern world.
Advantages of Flexible PCBs
Flexible printed circuit boards bring a myriad of advantages to the table, making them a preferred choice in modern electronics.
Flexibility and Adaptability
Space-saving Marvels
Durability and Reliability
Seamless Connectivity
What Are Flexible PCBs Used For?
In the changing world of medical devices, the role of flexible rigid printed circuit boards is crucial. These small electronic powerhouses help make devices smaller, meeting the evolving needs of the industry.
Medical Wearables: Flex PCBs find application in a variety of wearable health-tracking devices, such as blood glucose monitors, body temperature monitors, blood pressure monitors, heart monitors, etc.
Implantable Medical Devices: These refer to devices designed to be inserted into the human body, benefiting from the flexibility of PCBs for integration. Flex PCBs are used in various implantable medical devices such as pacemakers, neurostimulators, implantable cardiac defibrillators, and cochlear implants.
Hearing Aid Devices: Flex PCB designs enable the integration of microphone, digital signal processing (DSP), and battery components into a compact unit that fits discreetly behind the ear.
Diagnostic and Medical Imaging Equipment: such as ultrasound machines, MRI scanners, CT scanners, X-ray machines, and radiation treatment. The flexibility of Flex PCBs allows for compact and lightweight designs, which are crucial for portable and handheld diagnostic devices.
Endoscopic and Minimally Invasive Surgery Devices: Iin endoscopic cameras, catheters, and other minimally invasive surgical instruments the flexibility enables the creation of small, lightweight, and highly manoeuvrable devices that can navigate through the body’s intricate pathways with ease.
Overcoming Design Challenges
Flexible Printed Circuit Boards navigate and conquer unique design challenges, offering solutions that traditional rigid PCBs struggle to address.
Compact Design Challenge
Environmental Challenges
Integration in Small Devices
Reducing Complex Wiring
Conforming to Unique Shapes
Future Trends and Innovations
As technology advances, the trajectory of Flexible Printed Circuit Boards (Flexible PCBs) points towards exciting trends and innovations that will shape the future of electronic devices.
Internet of Things (IoT) Connectivity
Miniaturization and Integration
Advanced Materials
Biocompatible Applications
3D Flexible PCBs
Stretchable Electronics
Conclusion
Flexible printed circuit boards emerged as the key to revolutionizing electronic design. Their adaptability addresses real-world challenges, making them indispensable in medical IoT applications.
Future trends forecast even smaller, more versatile boards, promising a dynamic landscape in electronics.
Flexible PCBs are not merely components but architects of a connected, flexible future.
As we navigate this ongoing journey, the potential for innovation remains boundless, ensuring that flexible PCBs continue to play a transformative role in the ever-evolving realm of electronic devices.
With the proliferation of the Internet of Things (IoT) devices, there has been a huge transformation in terms of smart cities, connected manufacturing, wireless communication, and connected healthcare.
Embedded medical devices reduce the time to diagnose and treat patients effectively since these systems run on a high-speed processor with rich operating system interface.
These devices store data of each patient on the cloud and use them for different analysis and diagnosis purpose on a repetitive basis, decreasing the overall treatment turnaround.
How Embedded IoT Medical Devices Work
IoT medical devices work by connecting to different hardware for the diseases examination purpose. The device system has a touchscreen interface for users to input data for analysis and processing.
As a user inputs data related to the diseases, the system looks for symptoms pre-loaded into the file and tries to match with the provided input. If the match is found with the pre-loaded symptoms, the system responses with the disease name and generates a prescription for general medicine.
In case of a partial or no match, the system notifies to undergo a different test based on the input given by the user and pre-loaded file matching to identify the exact disease and provide prescription accordingly.
Prescriptions and other important details are stored on the cloud-based database management solution which can be used for future analysis. This patient information stored in the cloud can be also used for different analysis.
If proper disease information cannot be found by the given input and other tests performed, the system contacts the Doctor with the given information.
Workflow of IoT Medical Devices
User:
The user will provide the input via a touchscreen panel for the symptoms into Embedded Medical Device. The user also needs to provide all the personal information such as name, contact number, age, etc. Then, the embedded device will return generic medicine prescription for the disease found based on the input or contact the Doctor if the disease is not found.
Embedded Medical Device with IoT:
The embedded medical device receives inputs from the user to match the symptoms with a pre-loaded symptom file and tries to find the matching disease for same. It performs tests suggested based on the pre-loaded symptom file to get the exact match for the disease if the disease is not found by examining the symptoms. If the disease information is not found the system involves the doctor with the given information, who will consult the user, diagnose the disease and accordingly update the symptom file and disease file in the system.
Sensors used in Connected Healthcare Device:
Glucometer
Temperature Sensor
Blood Pressure Sensor
Airflow Sensor
ECG Sensor
EMG Sensor
Prescription for General Medicines:
Based on the input provided by the user, once the disease is found by the embedded medical device, it will look for generic medicine information in the pre-loaded prescription file, mapping the disease and medication.
Cloud Database Management System:
In this stage, the embedded device will store all the user details in the cloud database. This cloud-based solution can store the following information for future analysis:
User’s personal information
Information about symptoms
Information about tests performed and their results
Information about disease(s) diagnosedInformation about prescription and medication
Information about Doctor’s consultation if any
Device information from where all data is getting logged
Device health information on cloud just to make sure that device is working fine that includes all the sensor status and other basic information
Different analysis reports can be generated based on above information stored in the cloud for future use and preventive actions.
Conclusion
The embedded IoT medical devices are helpful in the area where basic healthcare facilities are not available.
Based on the disease analysis and data stored in the cloud, it helps users cure the diseases on time and also take preventive actions.
However, it is important to know that a continuous network connectivity is required to integrate the medical device with the cloud.
Medical devices must be compliant according MDR, IEC 60601-1/2/6, IEC 62304, 510K and ISO 13485.
AI and Robotics technology for applications and solutions are bringing high expectations to:
medical devices
wellbeing applications and devices
digital health platforms
diagnosis and analytics tools
surgery robots and control solutions
medical research analytics and results
healthcare processes and administration
Patient monitoring & management
IOMT Solutions
and a lot of more solutions and products
Generative AI tools and chatbots, for example, are cutting the time doctors and nurses spend on paperwork. Every day, we learn more about the potential of AI to improve healthcare.
One recent study by the UK’s Royal Marsden NHS Foundation Trust and the Institute of Cancer Research showed that AI was “almost twice as accurate as a biopsy at judging the aggressiveness of some cancers.” This translates into different treatments and, ultimately, more lives saved.
Today’s surgical robots extend surgeon’s capacities, they filter out hand tremors and allow manoeuvres that even the best surgeon couldn’t pull off with laparoscopic surgery’s typical long-handled tools. What will bring the future, will AI substitute surgeons?
Will robots run in future the tests and experiments inside the laboratory and be controlled via WEB page access?
Will AI accelerate drug discovery and boost personalized medicine and patient engagement?
Here some insight what we published in our Thaumatec Knowledge Database during the last years:
PACS, RIS, DICOM AND MIP are systems and standards of a digital, connected, data managing and analysing of Imaging technology systems and platforms. The goal is to collect, administrate, distribute, store, track and interpret health related Images from Radiology.
Additional to the Article in our Knowledge Database:
here some technology details of this systems with highlights and as well videos which explain more.
PACS means Picture archiving and communication system and is a medical imaging technology used primarily in healthcare organizations to securely store and digitally transmit electronic images and clinically-relevant reports.
It is used to store, retrieve, present and share images produced by various medical hardware modalities, such as X-ray machines, computed tomography (CT) scans, magnetic resonance imaging (MRI) scans and ultrasound machines. The storage media for PACS can be online (cloud storage) or offline (on-premises).
Every PACS has four major components:
Hardware imaging machines.
Secure network for the distribution and exchange of patient images.
Workstation or mobile device for viewing, processing and interpreting images.
Electronic archive for storing and retrieving images and related documentation and reports.
More insight:
RIS is a Radiology Information System with software that medics can use to keep better track of each patient being treated. It is the core system for the electronic management of imaging departments. The major functions of the RIS can include patient scheduling, resource management, examination performance tracking, reporting, results distribution, and procedure billing. RIS complements HIS (hospital information systems) and PACS (picture archiving and communication system), and is critical to efficient workflow to radiology practices.
Radiological information systems commonly support the following features:
Patient registration and scheduling
Patient list management
Modality interface using worklists
Workflow management within a department of radiology
Request and document scanning
Result entry
Digital reporting (usually using Voice Recognition (VR))[4]
Printables like patient letters and printed reports
Result transmission via HL7 integration or e-mailing of clinical reports[5]
Patient tracking
Interactive documents
Creation of technical files
Modality and material management
Consent management
More insight:
DICOM® means Digital Imaging and Communications in Medicine and is the international standard for medical images and related information. It defines the formats for medical images that can be exchanged with the data and quality necessary for clinical use.
This standard has been widely adopted by hospitals and the medical software industry, and is sometimes used in smaller-scale applications, such as dentists’ and doctors’ offices.
It is implemented in almost every radiology, cardiology imaging, and radiotherapy device (X-ray, CT, MRI, ultrasound, etc.), and increasingly in devices in other medical domains such as ophthalmology and dentistry. With hundreds of thousands of medical imaging devices in use, DICOM® is one of the most widely deployed healthcare messaging Standards in the world. There are literally billions of DICOM® images currently in use for clinical care.
DICOM® is recognized by the International Organization for Standardization as the ISO 12052 standard.
More insight:
MIP means Maximum intensity projection is a simple three-dimensional visualization tool and simple ray-tracing technique where the maximum intensity encountered along each ray within volumetric data is projected onto the screen.
That can be used to display computed tomographic angiography data sets.
MIP images are not threshold dependent and preserve attenuation information. is a simple ray-tracing technique where the maximum intensity encountered along each ray within volumetric data is projected onto the screen.
Imagine you’re tasked with urgently improving healthcare for people everywhere, and artificial intelligence (AI) promises to make a significant difference on a scale not seen in our lifetime. With the three options presented below, you can either:
1. Try to halt the development of AI until the risks and benefits are fully understood.
2. Go blazing into the unknown, deploying AI at every turn and dealing with issues as they arise.
3. Or fully embrace AI but take considered steps to limit the risks while unlocking the immediate benefits.
The general problems to be solved are
Many healthcare organizations are struggling to consistently deliver high-quality care.
There are more patients to look after and significant pockets of staff shortages, with doctors and nurses burdened by increasing clerical demands and complexity.
Costs are rising too.
Although many of us have received excellent care and great treatment, others struggle to access the care they need, especially people who live in under-resourced areas of the world
but also, increasingly, people living in wealthy urban areas.
We believe this crisis will only worsen unless we urgently deploy solutions that make a difference.
The good message is
AI can help, and it already has.
Generative AI tools and chatbots, for example, are cutting the time doctors and nurses spend on paperwork. Every day, we learn more about the potential of AI to improve healthcare. One recent study by the UK’s Royal Marsden NHS Foundation Trust and the Institute of Cancer Research showed that AI was “almost twice as accurate as a biopsy at judging the aggressiveness of some cancers.” This translates into different treatments and, ultimately, more lives saved. To learn about other developments on the horizon, consider some of the many predictions for what’s in store for 2024, from accelerating drug discovery to boosting personalized medicine and patient engagement.
But the goals are to be
(1) Harmonize the many sets of AI principles/frameworks/blueprints for healthcare and biomedical science. Identify and fill the gaps to create a best practice AI Code of Conduct with ‘guideline interoperability.’
(2) Align the field in advancing broad adoption and embedding of the harmonized AI Code of Conduct.
(3) Identify the roles and responsibilities of each stakeholder at each stage of the AI lifecycle.
(4) Describe the architecture needed to support responsible AI in healthcare.
(5) Define the identified ways to increase the speed of learning about how to govern AI in healthcare in service of a learning health system.
Conclusion
To achieve these goals and realize the full benefits of AI in healthcare while mitigating risks, it will take cross-sector collaboration and coalition building every step of the way – because we have a collective industry-wide responsibility to get this right.
Here the full Article by the World Economic Forum:
Medical device technology such as embedded medical systems consist of hardware and software customised for specific functions in medical devices. These technologies allow patients’ health to be monitored and managed frequently each day. For example, sensors extract data on aspects of a patient’s health, such as their heart rate, and send the data to physicians wirelessly for analysis.
Embedded systems are specialized computing systems designed to perform specific tasks within larger electronic devices or systems. They are omnipresent in our daily lives, present in a wide range of applications such as consumer electronics, automotive systems, medical devices, industrial machinery, and more.
These systems are characterized by their compact size, low power consumption, and real-time operation. They typically consist of a microcontroller or microprocessor, memory, input/output interfaces, and various sensors or actuators. Embedded systems enable the seamless integration of technology into our surroundings, enhancing functionality and efficiency.
They play a crucial role in enabling smart and connected devices, automation, and the Internet of Things (IoT). As technology advances, embedded systems continue to evolve, driving innovation and shaping the future of various industries.
The Market Prognosis Highlights Embedded Systems
The Global Embedded System Market Size was valued at USD 156.35 billion in 2022.
The market is growing at a CAGR of 5.3% from 2023 to 2032
The global embedded system market is expected to reach USD 262.05 billion by 2032
Asia-Pacific is expected to grow the fastest during the forecast period
Medical Embedded Systems play more and more a key-role.
Market Overview
Driving Factors
The embedded system market is driven by several factors, including increasing demand for connected devices and the Internet of Things (IoT), the growing use of automation in various industries, and the need for real-time computing and control.
Additionally, the expansion of the automotive industry and the growing demand for smart home devices are also driving the growth of the embedded system market. The increasing adoption of wireless technologies and the need for enhanced security in embedded systems also contribute to market growth.
Furthermore, the rise of artificial intelligence (AI) and machine learning (ML) is driving the development of more sophisticated embedded systems that can support these technologies. The emergence of new technologies, such as 5G, also presents opportunities for growth in the embedded system market, as these systems will need to support these technologies and operate in real time.
Restraining Factors
The embedded system market faces certain restraints that can hinder its growth. These include the complexity and cost of development, as creating embedded systems requires specialized skills and resources.
Additionally, the market is highly fragmented, with a wide variety of hardware and software platforms, making interoperability and standardization challenges.
The limited processing power and memory capacity of embedded systems can also pose limitations on the functionality and performance they can deliver.
Moreover, concerns related to security and privacy can impede the widespread adoption of embedded systems.
Lastly, the lifecycle of embedded systems is often long, leading to slower technology refresh cycles and potential compatibility issues with newer technologies.
Market Segments
Embedded System Components
Hardware
Software
On the basis of the component, the global embedded system market is segmented into hardware and software.
The hardware segment is dominating with the largest market share in 2022, this dominance can be attributed to the crucial role hardware components play in the functioning of embedded systems. Hardware components include microcontrollers, microprocessors, sensors, memory devices, and other electronic components that form the core of embedded systems.
These components are essential for processing, storing, and interacting with data, enabling the embedded system to perform its intended functions.
Embedded System Functions
Standalone system
Real-time system
Network system
Mobile system
The hardware segment’s dominance is further driven by the continuous advancements in semiconductor technology, leading to more powerful and efficient hardware solutions.
Medical device technology
Medical device technology and embedded solutions are essential for the medical device industry.
Examples of applications of embedded systems in the medical field include imaging systems such as magnetic resonance imaging (MRI) and computed tomography (CT), defibrillators, blood pressure monitoring devices, digital flow sensors, foetal heart monitoring machines, and wearable devices.
Embedded technology suppliers for medical devices
Medical Device Network has listed leading embedded technology suppliers, based on its intel, insights, and experience in the sector. The list features specialists in customised embedded boards and industrial platforms, semiconductor solutions for medical applications, printed circuit boards for the medical market, and other solutions.
Main TIER1/TIER2 Players:
Intel Corporation
Renesas Electronics
Texas Instruments Inc.
NXP Semiconductors
Qualcomm Incorporated
Cypress Semiconductors
Infineon Technologies
Analog Devices Inc.
Microchip Technology Inc.
STMicroelectronics N.V.
Samsung Electronics
On Semiconductor
Toshiba Corporation
Medical grade embedded technologies
Embedded systems generally incorporate an operating system and a processor to allow them to react in real-time with limited resources, especially in highly critical situations.
These systems include microprocessors, digital signal processors (DSP) or converter microcontrollers, memory for data storage, sensors, actuators, and other interfaces.
Medical grade embedded technologies are constantly being updated to reduce their size, increase their processing power, and incorporate programmed automatic technologies to provide improved treatments and medications for patients.
Embedding medical systems with the Internet of Things (IoT)
Medical systems with embedded Internet of Things (IoT) capabilities can help address shortages of doctors in remote locations. These systems’ operating system interfaces and high-speed processors can expedite diagnosis and treatment times for patients.
Embedded IoT medical devices can be connected to various hardware items and store patients’ data on the cloud to be analysed and used by clinicians, whenever necessary.
Other Embedded System Applications
Based on the application, the global embedded system market is segmented.
Automotive
Consumer Electronics
Manufacturing
Retail
Media & entertainment
Military & Defense
Telecom
North America and Embedded Systems
Based on region, North America is the largest market for embedded systems, accounting for the highest share of the global market. The region’s dominance can be attributed to several factors, including the presence of established players, a high level of technological advancement, and the growing demand for connected devices and IoT applications.
The region has a strong focus on research and development, with significant investments in developing new technologies and expanding the application of existing ones.
Additionally, the region has a high level of consumer spending on healthtech, electronics and home automation, which further drives the demand for embedded systems.
Key Target Audience
Market Players
Investors
End-Users
Government Authorities
Consulting and Research Firm
Venture Capitalists
Value-Added Resellers (VARs)
Conclusions
Overall, the Embedded System Market is expected to continue to grow as technology advances and new applications for embedded systems emerge.
Medical device technology and embedded solutions are essential for the medical device industry.
Overall, the combination of factors positions North America as a dominant market for embedded systems and is expected to continue to drive growth in the coming years.
If you want to get more insight have a look at the Article of Medical Device Network:
Economic crisis, inflation and rising prices cast a long shadow over the new year. What will the future of the medical technology market look like in 2024?
#1 Cost back to number one
Medical technology in Germany is under enormous pressure – enormous cost pressure. Two thirds of the MedTech companies in Germany expect better sales results than in 2022, but this does not yet come close to the pre-pandemic years. With an average increase in sales of 4.8 percent, the German market is also performing significantly worse than the rest of the world (6.4%).
Medical technology manufacturers are putting the brakes on investments and cutting R&D spending, and many are closing their domestic production facilities because energy prices, personnel costs and compliance costs are rising.
#2 Outsourcing becomes a question of survival
Rather, in 2024, manufacturers will continue to outsource their development, production and supply chain, integrate external partners more closely into their own team of employees and place as much of the bureaucratic compliance effort in the hands of third parties as possible.
Through outsourcing, companies also gain the much-needed flexibility and speed to innovate in the current competitive environment and focus on their core competencies.
This strategy becomes a question of survival, especially for small and medium-sized companies (SMEs), which make up 93 percent of the industry.
This brings new challenges to the fore. Anyone who relocates their production to lower-cost countries must meet high quality and compliance standards and also ensure these “remotely”.
Outsourcing is not an ad hoc solution. A long-term strategy and a careful selection of the partner network are therefore crucial.
#3 Supply Chain: Resilient but highly bureaucratic
Delivery bottlenecks remain a nuisance. However, a radical realignment of the supply chain – as was conceivable two years ago – no longer seems necessary.
The semiconductor market is an example of this upward trend. The second half of 2023 already saw an improvement in supply and availability. Lead times, costs and market dynamics appear to be stable so far. This trend is likely to continue in the coming months.
From January 1, 2024, the Supply Chain Due Diligence Act (LkSG) will apply in Germany for the first time to companies with more than 1,000 employees. An even stricter law is set to come into force at EU level in the next few months. The draft guidelines for this were already adopted in the summer of 2023.
#4 AI: From trend to technology transition
A topic that should not be missing from any trend list in 2024 and is also gaining importance in medical technology is artificial intelligence (AI). The legal framework for safely using AI technologies in such a highly sensitive area as medicine and healthcare is either incomplete, immature or a long time coming. The Artificial Intelligence Act (AIA for short), passed in June 2023, for example, will probably only take effect in two to three years at the earliest.
However, MedTech companies must now develop an AI strategy if they want to benefit from the technology and remain competitive.
AI is more than just a chatbot à la ChatGPT. Artificial neural networks (ANN) trained with photos can already classify melanoma and carcinoma and detect skin cancer at an early stage. Surgical robots use computer vision to distinguish between different types of tissue.
Large Language Models (LLMs) simplify access to important information for physicians. And generative AI (GenAI) relieves the burden on medical specialists and nursing staff in the healthcare system when it comes to documentation and monitoring.
For MedTech manufacturers, in addition to boosting product innovation, AI has a massive impact on manufacturing, development and supply chain. Because with and through AI, AI solutions for medical technology can also be developed, implemented and brought to market more quickly. In the semiconductor market, for example, in the future Microsoft AI will take over the design of the planned Microsoft AI chips itself. In the next few years, manufacturers will increasingly invest in the AI suitability of their locations or, alternatively, rely on partners with the appropriate capacities and know-how.
#5 Sustainability is no longer a USP in medical technology
The social, economic and ecological footprint of medical technology remains large. According to the SEE Impact Study, the industry is responsible for emitting 8.9 million tons of greenhouse gases in Germany alone. Over 60% of emissions occur indirectly in global supply chains.
The demand for product sustainability solutions has been increasing continuously for years and is growing in parallel with regulatory requirements in the EU.
In the future, decarbonization strategies will therefore focus more on all phases of the product life cycle.
Sooner or later, however, sustainability will lose its unique selling point and become the norm.
#6 Compliance mix: MDR, GDNG & Co.
The bureaucratic and regulatory pressure on medical technology will continue to increase in 2024. In addition to cross-industry requirements on supply chain, sustainability, cybersecurity and the use of AI, MedTech manufacturers are still struggling with the implementation of the EU Medical Device Regulation (MDR).
A bright spot in the compliance jungle, however, is the Health Data Use Act (GDNG). The draft is intended to reduce bureaucratic and organizational hurdles in data use without endangering data protection.
See more details in the article on digital health industry
Recent advances in radiology include better image quality, the use of functional data, and enhanced quantitative analysis.
The radiology industry embraces transformative technological advancements such as the integration of artificial intelligence (AI) and machine learning into imaging equipment and analytical tools.
Trends in 2023
Artificial Intelligence and Machine Learning in Radiology
Because radiology is a data-driven specialty, it is well-suited for AI applications. AI was first used in healthcare in 1976 when clinicians used an algorithm to help diagnose intense abdominal pain. Today, the use of AI and machine learning is common across a range of radiology applications.
In 2023, the efforts to integrate AI and machine learning into imaging equipment accelerated, with products boasting built-in capabilities.
Companies like GE Healthcare, Philips, and Siemens Healthineers are rapidly ramping up the rate of new software radiology products using artificial intelligence is.
The vast majority of today’s image interpretation software applications tend to fit into three categories:
Diagnostic
Repetitive
Quantitative
Today, AI is used in healthcare to help detect, classify, and predict diseases. Already, AI is commonly used to detect diseases of the head and neck, breast, chest, and more. Even so, AI is still in the early stages of development in healthcare. New opportunities, such as mitigating workforce shortages, evaluating mental illness, and managing medical triage are ready to be harnessed.
Predictive Analytics
In 2023, imaging departments and imaging centres saw synergy between innovation and efficiency through the use of predictive analytics. The results for many radiology departments were improvements in operational efficiency and other key performance indicators (KPIs).
Many imaging centres don’t streamline their efficiency because they are unable to quantify what changes they need. From the Example above, without proper analytics, an imaging centre may not realize that they typically complete a given exam in less time than scheduled. They can miss the opportunity to harness that extra time to increase the number of profitable exams they fit into the day.
A key component in maximizing operational efficiency is through the reduction of variation. Using predictive analytics can enable leaders to identify patterns, optimize workflows, and standardize procedures through historical data. By better understanding workflow, radiology departments can deliver better patient experiences and financial outcomes.
In the past year, predictive analytics tools have become increasingly recognized as critical to understanding patient behavior patterns and imaging department needs. According to McCall, “Predictive analytics can tell you when patients generally arrive late to appointments, and when they tend to arrive early. You can predict how many cancellations to expect.”
Wait time is a big contributor to satisfaction levels. According to a recent poll, 28% of patients admit to leaving the office without seeing the doctor due to long wait times, followed by 26% changing doctors. Additionally, patients warned friends and family not to go to the office, left negative survey reviews, and published negative online reviews, potentially damaging a radiology center’s reputation. Using relevant analytics, radiology departments can streamline operations and minimize wait times, while increasing retention rates, patient satisfaction, and revenue.
Imaging Department Operations and Clinical Services
Operational challenges continued to evolve in 2023, including workforce shortages, mixed-age fleet challenges, and site inefficiencies.
The continued rise of AI and machine learning in 2023 has brought about meaningful advances in research and development, diagnosis, patient prognosis, surgery, and more. Newly available data sets of annotated images have helped advance training and testing. Imaging equipment manufacturers such as Canon, GE Healthcare, Philips, and Siemens Healthineers are focusing on new ways to use AI technology in radiology.
Fueled by advanced algorithms and machine learning, AI has helped bring about advances in DICOM image quality, speed, and interpretation. AI algorithms are helping radiology departments better care for patients while expediting the process.
Currently, many radiology departments are coming to embrace AI to enhance diagnostic capabilities and create a more efficient workflow. This new level of acceptance and use of AI and machine learning is reflected in our 2024 forecast.
Medical Imaging Trends in the 2024 Forecast
Looking forward to 2024, we expect to see accelerating growth in using predictive service analytics to streamline imaging department operational efficiency and to set and track effective KPIs. Utilization analytics will be critical in creating sophisticated planning and streamlined operations to minimize costs and maximize revenue potential.
Large company investments and venture capital funding in AI development of radiology applications is expected to increase, as investors are realizing the potential size of the market. Many small software start-ups as well as major manufacturers of medical imaging equipment — such as Canon Medical, GE Healthcare, Philips and Siemens Healthineers — will continue to develop AI tools that positively impact diagnosis speed and accuracy.
In 2024, we expect DICOM-compatible AI tools to expand into new healthcare applications, as well as improve their diagnosis algorithm accuracy. Radiologist confidence in AI tools is expected to improve over time as well.
Imaging Industry Trends Conclusion
The journey from 2023 to 2024 promises to be one of adaptation, innovation, and data analysis.
Workforce shortage challenges are expected to continue, with additional solutions to this ongoing challenge coming to market.
With 2024 being an election year, the radiology industry will brace for a slowdown, while contemplating the potential impact on reimbursement and consolidation. Staying informed and open to new technologies from small software companies as well as large equipment manufacturers such as Canon Medical, GE Healthcare, Philips and Siemens Healthineers will be critical for radiology departments to thrive in this evolving landscape.
Digital health includes digital care programs and technologies for health, healthcare, living, and society. It enhances the efficiency of healthcare delivery and to make medicine more personalized and precise.
It uses information and communication technologies to facilitate understanding of health problems and challenges faced by people receiving medical treatment and social prescribing in more personalised and precise ways.
Worldwide adoption of electronic medical records has been on the rise since 1990 and is closely correlated with the existence of universal health care.
Generally, digital health interconnects health systems to improve the use of computational technologies, smart devices, computational analysis techniques, and communication media to aid healthcare professionals and their patients manage illnesses and health risks, as well as promote health and wellbeing.
Digital health technologies include:
Hardware
Software solutions
Services
Telemedicine
Wearable devices
Augmented reality
Virtual reality
Although digital health platforms enable rapid and inexpensive communications, critics warn against potential privacy violations of personal health data and the role digital health could play in increasing the health and digital divide between social majority and minority groups, possibly leading to mistrust and hesitancy to use digital health systems.
Digital Health Elements
The prominence of Digital health in the past century has culminated for the emergence of three reasons:
Primary Care Services
The first group of these services is known as primary care services in the domain of digital health. These services include wireless medical devices that utilize technology such as Wi-Fi or Bluetooth, as well as applications on mobile devices that encourage the betterment of an individual’s health as well as applications that promote overall general wellness.
Acute Care Services
The second group of these services is known as acute care in the digital health domain. These services include telemedicine which is defined as handling patients over some sort of streaming device and is targeted towards areas where the population is more widely scattered, medical devices that incorporate different aspects of software otherwise known as SaMD, and examples of these devices are pacemakers.
Digital Health Information solutions and Applications
The rest of the elements of Digital health that do not fall so squarely into acute or primary care services are listed as the transmission of medical education and information between practitioners and researchers through the utilization of digital technologies and applications that can be employed by doctors for risk-assessment regarding patients.
Devices that can be utilized for the improvement and management of bodily purposes as well as the encouragement of the education of digital health to the public.
There are also patient-based applications that can be utilized to share information by individual patients as well as encourage the usage of drug trials. The tracking of outbreaks of disease by the use of mass media that social media has developed has also come about through Digital Health.
Finally the recording of the environment around sensor devices that are being utilized for the betterment of the community.
Technologies
Digital health technologies come in many different forms and extend into various parts of healthcare. As new technologies develop, digital health, as a field, respectively transforms.
In fact some of these technologies are being propelled by the startup space, which has been followed via Internet or online media sources such as podcasts on digital health entrepreneurs.
The National Institute for Health and Care Research (NIHR) has published a review of research on how digital health technologies can help manage health conditions.
One of the Technology areas is Internet of Medical Things (IOMT)
The Internet of Medical Things (IOMT) is the network of Internet-connected medical devices, hardware infrastructure, and software applications used to connect healthcare information technology.
Due to several stakeholders the IOMT solutions have to serve multiple Users and Interest groups with different knowledge and skills.
Therefore these solutions have to be shaped carefully in usability, security and safety and according Medical Device Regulations (MDR) or US Food and Drug Administration (FDA) classifications and some, depending on classification level, have to be approved by clinical trial results.
Here a short check list of the main User Impact areas:
Many of the most innovative digital Health ideas products are based on IOMT Technology.
Many new ideas are challenging and start-ups with many aspects of monetisation, market impact, user impact, value add, and how to apply the findings to this idea and the technology properly.
Here some check points for the entrepreneurs of IOMT digital Health solutions:
One example of the IOMT Technology based Digital Health Applications is Telemedicine
Telemedicine is one of the broadest areas of digital health. It encompasses the digitization of medical records, remote care, appointment booking, self-symptom checkers, patient outcome reporting, and many others.
Digital and remote clinics are commonly used to provide quick, nonurgent consultations that save both the patients and doctors time. Especially with the COVID-19 pandemic, this type of treatment has become the primary way doctors are seeing their patients and may be as effective as face to face appointments.
This type of digital treatment keeps both parties safe and is a reliable method that physicians plan to use for routine checks even after the pandemic ends.
Another example of IOMT in digital Health are Wearables
Wearable technology comes in many forms, including smartwatches and on-body sensors. Smartwatches were one of the first wearable devices that promoted self-monitoring and were typically associated with fitness tracking.
Many record health-related data, such as “body mass index, calories burnt, heart rate, physical activity patterns”.
Beyond smartwatches, researchers are developing smart-related bodywear, like patches, clothes, and accessories, to administer “on-demand drug release”.
This technology can expand into smart implants for both severe and non-severe medical cases, where doctors will be able to create better, dynamic treatment protocols that would not have been possible without such mobile technology.
These technologies are used to gather data on patients at all times during the day. Since doctors no longer need to have their patients come into the office to collect the necessary data, the data can lead to better treatment plans and patient monitoring. Doctors will have better knowledge into how well a certain medication is performing. They will also be able to continuously learn from this data and improve upon their original treatment plans to intervene when needed.
Digital Health innovations combining Augmented-, Virtual Reality and IOMT Technology
IOMT Technology combines many different sensors, connects devices and delivers data and streams videos to central health care observation and safety points e.g. for Remote Patient Monitoring and Remote Patient Management (RPM).
As well the provision of rehabilitation programs, trainings and also patients condition check makes IOMT Tech possible.
Augmented Reality
In digital health, augmented reality technology enhances real-world experiences with computerized sensory information and is used to build smart devices for healthcare professionals.
Since the majority of patient-related information now comes from hand-held devices, smart glasses provide a new, hands-free augmented way for a doctor to view their patient’s medical history.
The applications of this technology can extend into data-driven diagnosis, augmented patient documentation, or even enhanced treatment plans, all by wearing a pair of smart glasses when treating a patient.
Virtual Reality
Another similar technology space is virtual reality, which creates interactive simulations that mimic real-life scenarios and can be tailored for personalized treatments.
Many stroke victims lose range of motion and under standard treatment protocols, Other patients have long-term upper muscular dysfunction, as the lower body is primarily targeted during therapy.
Repeated actions and the length of therapy are the two main factors that show positive progress towards recovery. Virtual reality technologies can create various 3D environments that are difficult to replace in real-life but are necessary to help patients retrain their motor movements. These simulations can not only target specific body parts, but can also increase in intensity as the patient improves and requires more challenging tasks.
Innovation cycle
The innovation process for digital health is an iterative cycle for technological IOMT solutions that can be classified into five main activity processes from the identification of the healthcare problem, research, digital solution, and evaluating the solution, to implementation in working clinical practices.
Digital health may incorporate methods and tools adopted by software engineering, such as design thinking and agile software development.
These commonly follow a user-cantered approach to design, which are evaluated by subject-matter experts in their daily life using real-world data.
Conclusion
IOMT is an essential building block for many digital Health applications and solutions. New innovative ideas have to be checked and proved carefully. If the right experts combine and integrate MIOT with other Technologies great products are to predict.
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