RMIT University

Researchers from Asan Medical Center, one of South Korea's largest hospitals, have developed a generative AI model that can autonomously learn and analyse brain scans to diagnose and predict the progression of Parkinson's disease. The research team built a foundational model that can learn from a large database of dopamine transporter positron emission tomography (DAT PET) images to diagnose Parkinson's disease, predict its progression, and create prognostic images. DAT PET imaging has high sensitivity and specificity for detecting dopamine transporters, which can aid in the early diagnosis of Parkinson's disease and related disorders. Their model, called Hierarchical Wavelet Diffusion AutoEncoder (HWDAE), creates a hierarchical representation of these images; approximately 1,934 DAT PET images were utilised in training the model. The AMC researchers later tested the AI to differentiate Parkinson's disease from essential tremor, multiple system atrophy, and progressive supranuclear palsy and to predict the time of onset of Parkinson's motor symptoms. FINDINGS The researchers reported in a study published in Cell Reports Medicine that their AI model could distinguish Parkinson's from essential tremor with 99.7% accuracy and from multiple system atrophy and progressive supranuclear palsy with 86.1%% accuracy. It also showed a coefficient of determination of 0.519 in predicting symptom onset, which signifies a high prediction accuracy. Additionally, the team confirmed that the model maintained its performance when trained and tested using brain scans generated from other PET devices at AMC and other hospitals. WHY IT MATTERS Besides improving how Parkinson's disease is diagnosed at an early stage, the AMC AI model can provide analysis that informs treatment decisions by medical teams and supports them in explaining to patients the possible disease progression. "This is a groundbreaking technological advancement that can increase the accuracy of Parkinson’s disease diagnosis. Since it can produce predictive images of the prognosis of the disease that patients are most curious about, I expect that it will [become a tool that] can provide practical help to patients in clinical practice in the future," commented Sun-ju Chung, one of the study's authors and a professor at AMC Department of Neurology. The research team now plans to apply their AI model to other neurodegenerative diseases, according to one of its members, Professor Kim Nam-guk of the AMC Department of Convergence Medicine. THE LARGER TREND Recent studies across Asia-Pacific have demonstrated the application of AI in mobile technologies for diagnosing Parkinson's disease. A study by RMIT University researchers in Australia showed how an AI-driven application analyses voice records to detect Parkinson's. King Chulalongkorn Memorial Hospital in Thailand tested a similar AI-powered app that screens for Parkinson's by also evaluating voice records, as well as finger movements, tremors, and balance. The Alfred Hospital in Melbourne, Australia, has also recently started studying a digital eye movement test to detect and monitor neurological disorders, such as Parkinson's disease. Meanwhile, the South Korean government intends to develop a foundational model for assessing cognitive decline as part of projects under the Korean Advanced Research Projects Agency for Health this year.

FaceHeart from Taiwan has obtained regulatory approval in the United States for its AI-driven contactless technology for measuring respiratory rate. It obtained a 510(k) clearance from the US Food and Drug Administration for the respiratory rate measurement component of its software development kit. WHAT IT'S ABOUT FaceHeart offers a SDK that utilises a smartphone's camera to capture vital signs – including heart rate, respiratory rate, blood pressure, oxygen saturation, and heart rate variability – and measure them within 50 seconds. It does this using computer vision, rPPG (remote photoplethysmography), and deep learning. Citing FDA's evaluation, the company shared that its SDK's respiratory rate component demonstrated consistent deviations within ±2 breaths per minute across devices. This FDA approval is the company's second following the 510(k) clearance for the heart rate component of the FaceHeart SDK in 2023. The Taiwanese company's SDK can be integrated into common edge devices, such as smartphones, tablets, and desktop or laptop computers, and conducts analysis using edge computing without a cloud service to maintain security and eliminate network latency. The technology has use cases in preventive health, telemedicine, elderly care, and chronic disease management. MARKET SNAPSHOT Several smartphone-based applications that utilise PPG signals to gauge vital signs have also come to the market in recent years. Noteworthy among them is Google Fit. In Asia-Pacific, notable players include MFine from India and listed company Advanced Health Intelligence (formerly Advanced Human Imaging) from Australia. The National Taiwan University Hospital in Taiwan and its partner, FocalTech Smart Sensors Co., also developed a mobile app that measures heart rhythm by scanning a user's fingertip via a smartphone camera. Meanwhile, Canadian company NuraLogix's Anura vital signs measurement app has been made available in Singapore. Another popular use of smartphone cameras for health screening is to detect and predict stroke, such as the inventions of Penn State University and Houston Methodist Hospital in the United States and RMIT University in Australia.

Just a few decades ago, for a patient to gain insight into their current health prognosis, they would have to set up an appointment with their provider. They would then get lab tests, wait for the doctor to read them, and then communicate the results to the patient. Long, drawn-out processes limit immediate care opportunities. For those who manage chronic diseases and may be living at home or in a nursing facility, the use of wearable health tech can drastically improve patient-doctor care. It may even help to save a person’s life over time. A study from the University of Queensland, Brisbane, Australia, found that the use of wearables within a healthcare setting and at home for chronic disease management improved odds. Wearable devices, such as a glucose meter device or a defibrillator and pacemaker, can provide valuable and real-time information to a healthcare provider so that decisions can be made to protect the patient. These devices typically provide a very specific type of service, such as capturing the blood sugar of a patient. They link to Wi-Fi and transmit data directly to a healthcare provider, and that provider can take action if needed to bring the patient in for care. Sponsored Post The Funding Model for Cancer Innovation is Broken — We Can Fix It Closing cancer health equity gaps require medical breakthroughs made possible by new funding approaches. By Eve McDavid - CEO of Mission-Driven Tech Innovations in wearable health tech for chronic conditions Science and technology come together with wearable devices, providing a clear benefit to anyone who may need careful and tedious management of disease symptoms. Gone are the days when a simple heart rate monitor or pedometer would provide the only information about a person’s health and well-being. Today, they can accomplish a wide range of tasks: Determine sleep quality and quantity Provide a heart rate and rhythm analysis Measure blood glucose levels Provide respiration management Monitor blood pressure Complete electrocardiograms Check for fevers presented by Market Trends to Watch for Health Systems and Their Specialty Pharmacies The future looks bright for the integrated specialty pharmacy model – for health systems, providers, and most importantly, for patients. By Jake Gaffey, MBA, Chief Strategy Officer at Shields Health Solutions Consider the benefits. For example, the use of a glucose meter can capture a patient’s blood glucose figure and transmit that information to the person’s healthcare provider. If that patient is just coming on board for treatment through medication, this type of wearable technology enables doctors to pinpoint what’s causing the blood sugar spikes or if a specific medication level is appropriate. When choosing a glucose meter, it’s crucial to consider various factors such as accuracy, ease of use, and data sharing capabilities to ensure seamless integration with overall health management Another example could center around sleep. Instead of a patient visiting a medical center for a sleep study that is fully uncomfortable and challenging to maintain, they can use a wearable device at home. These devices can track sleep quality and quantity, allowing medical providers to have more insight into what the patient’s complications may be. Benefits of wearable health tech for patients Many types of diseases change in severity from one appointment to the next. Yet, there’s often a lot of leeway in between those situations. Consider a few examples of how wearable health tech is transforming the way healthcare providers monitor and support chronic health conditions. Improve patient engagement – Not only do devices communicate valuable health data, but they also help patients to routinely monitor their own health data. This helps patients to remain engaged in their health. Reduces healthcare cost – Fewer trips to the emergency room or urgent care, along with improvements to efficient management of chronic conditions, and reduced overall costs. Patients get help when they need it, sometimes before there is a medical emergency. Health monitoring over time – Those with chronic disease face an ongoing risk of the condition worsening. With a wearable device, documents can see the slow progression or climb of the health complication, providing a way for the patient to get help sooner. Wearable technology is better than relying on human information – If a patient’s blood sugars must be monitored to determine proper medication, it is easier to count on wearable technology to support this process instead of assuming a patient will document their information. Improved health – Another side benefit of the use of wearable technology is that it offers patients more insight into their own health. For example, a notification that they are not getting good sleep may help a person to change their habits. Increasing step counts could also be helpful here. Wearable health technology challenges and limitations Numerous potential factors cloud the benefits wearable health technology seems to offer, at least if no other steps are taken to mitigate those risks. Some of the most common challenges with healthcare wearable technology include: High initial cost – It can be challenging to get insurance providers to consistently pay for these wearable devices. New programs are emerging to make them more accessible. Data privacy concerns – If the system is not secured and maintained over time, this can lead to serious loss of personal information. Modern solutions utilize encryption to eliminate such risks. Accuracy and reliability factors – Utilization of high-quality and reliable tools and then educating patients on how to properly use them is critical to finding success with wearable technology. Future trends in wearable health tech for chronic disease management The world of technology continues to flex and change, bringing with it new opportunities for advancement in wearable technology. Studies show that wearables empower users to get better care and take responsibility for their health. In the future, such tools may provide more hands-on recommendations, such as dosing for insulin shots based on monitored levels. They can also incorporate more data-rich insights to allow doctors and patients to get a better idea of how their health is trending. Wearable technology provides a clear opportunity for improving overall health and well-being. That is especially true in the area of chronic disease management. Photo credit: Sitthiphong, Getty Images Steven John CumperSteven John Cumper, B.App.Sc. (Osteo.), M.Ost., is a businessman with a strong background in biomedical science and osteopathic medicine. He founded Medshop & ScrubsIQ while studying at RMIT University in Australia, expanding its reach to markets in Papua New Guinea, Singapore, and Malaysia. In September 2021, the Bunzl Group acquired a majority stake in Medshop, but Cumper remains involved as the Managing Director (Medshop Group). His journey from Zimbabwe to the UK and Australia reflects his dedication to academia and entrepreneurship, combining diverse knowledge and experience.This post appears through the MedCity Influencers program. 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