Researchers at the University of Leuven in Belgium said a study they conducted showed artificial intelligence could help interpret, and thereby improve, lung function tests used to diagnose long-term lung disease. Results of the study were presented Monday at the European Respiratory Society's International Congress. As part of the study, the researchers used data from 968 people who were undergoing complete lung function testing for the first time. Using a concept called "machine learning", they developed an algorithm that takes into account routine lung function parameters and clinical variables of smoking history, body mass index, and age to make a suggestion for the most likely diagnosis. "We have demonstrated that artificial intelligence can provide us with a more accurate diagnosis in this new study," Wim Janssens, senior author of the study, said.
Since the dawn of man, we have always been looking for ever more accurate methods of solving problems. The rise of big data has certainly been a big help. Typhoon forecasts and the treatment of diabetes, though totally unrelated, are two examples of how technology can make a big difference. The Chinese word for typhoon was first used in the late Ming Dynasty. In the old days, people used wind direction and abnormal animal behavior, such as deep-water fish coming near the shore, to forecast the arrival of a storm.
Medical device maker Medtronic and Novo Nordisk have entered a collaboration pact to develop ways of integrating insulin dosing management data from future Novo Nordisk smart insulin pens into Continuous Glucose Monitoring (CGM) devices from Medtronic. Novo Nordisk plans to launch the NovoPen 6 and NovoPen Echo, durable smart insulin pens, along with disposable, pre-filled injection solutions, in 2020. These smart insulin pens will be compatible with both Android and iOS devices. The collaboration, which is non-exclusive, will allow them to be compatible with Medtronic CGM, such as the Guardian Connect system. In addition to being able to better track and manage blood glucose levels, healthcare professionals and caregivers, with permission from the patient, can automatically track glucose monitoring and insulin dosing data in a single location.
An artificial pancreas which allows diabetes sufferers to lead'normal lives' could be available within two years. Scientists have developed an iPhone-sized device which monitors patients' blood sugar levels and automatically injects the right levels of insulin. The revolutionary product attaches to the wearer's clothing from where it monitors glucose levels and provides insulin when required through patches on the skin. It could prove a lifeline for around 350,000 Britons who suffer from Type 1 diabetes – a lifelong condition where the pancreas stops producing insulin. Currently, patients must inject themselves with insulin up to five times a day to avoid serious health problems.
Recent years have seen an explosion in the field of health apps, wearable devices and sensors monitoring many aspects of health and fitness. With an ageing population and the rise in multiple chronic conditions, demands on the health and social care system are increasing. Improving prevention and empowering patients to manage their own health can be successful strategies to eventually reduce financial pressures and improve patient outcomes. With some caution and appropriate patient safety checks, sensors and devices connected through the Internet of Things (IoT) can be great tools to deliver enhanced prevention, early diagnosis and the self-management of chronic conditions. But how far can sensors and wearables really take us in delivering such goals?