Artificial intelligence is now being applied to patients to diagnose diseases well before symptoms even begin. The well-versed term ‘prevention is better than cure’ may finally come to realization. Technology is being developed to track potential health conditions in at risk populations. With the use of AI a patient’s heart rate, breathing, the way they move and much more can be analyzed to identify health issues, health professionals can then offer health promotional lifestyle advice to allay or prevent the illness. An incredible example of this is from researches at Google who applied AI algorithms to retina scans of almost 300,000 patients and discovered a predictor for cardiovascular disease. Their findings suggest that regular eye scans can provide indications for risk of heart attacks, allowing professionals to intervene and offer preventative medication and lifestyle changes.
Dina Katabi, a Professor of Electrical Engineering and Computer Science at MIT and the director of the MIT Wireless Center goes that step further. Her technology sits in the walls of your home and transmits low-level wireless signals that reflect off a person’s body returning vast amounts of data back. This data is said to provide cues for future illness before the person even knows themselves. Katabi suggests that such technology is essential to support our aging population, often living alone, currently placing a significant demand on emergency medicine services.
A Company called Face2Gene also utilizes deep learning AI technology to predict rare genetic disorders based on a person’s face shape. FDNA have created an app that has learned to identify facial hallmarks of conditions often missed by doctors. This early diagnosis of these often-misdiagnosed genetic syndromes can ensure correct treatment is provided and spares families unnecessary testing and interventions.
Ben Franc a radiologist at Stanford University has been using AI techniques in a recent study using PET scans to analyze brain metabolism. Current results from the study have diagnosed Alzheimer’s six years before a human doctor. Franc explains that computer algorithms can find associations in patient data that would take medics a lifetime to find. This exposure to millions of patient’s information allows early diagnosis and timely treatment. His team have also been using radiomics to identify breast cancer using PET and MRI scans. This raw data allows the essential early diagnosis and has led to multiple cases of recurrence-free survivors.
Need I say more? If the medical world embraces the significant impact of AI technology on their ability to protect and care for their patients, the annual check-up could be obsolete. The real question is, how much trust can we put into a computer algorithm and do we need the bedside manner of a human doctor? With 91% of Face2Gene facial recognition software being correct and AI technology being trained to respond to human behavior, these will soon be worries of the past!
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