By analyzing Fitbit data and self-reported symptoms, researchers analyzed trends in heart rate, step count, and symptom duration between patients with flu and those with COVID-19.
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For the first time doctors have shown that measuring changes in 24-hour heart rate can reliably indicate whether or not someone is depressed.
Researchers develop new machine learning approach that shows promise in predicting Necrotizing enterocolitis; could lead to improved medical decision-making in neonatal ICUs.
Researchers have developed a "smart" contact lens that can show real-time changes in moisture and pressure by altering colors.
How University of Alberta health scientists are helping fulfil the promise of big data to revolutionize everything from prevention to diagnosis to treatment.
More researchers and companies are moving into the brain-computer interfaces, yet major challenges remain, from user training to the reality of invasive brain implant procedures.
An artificial intelligence-based detects early stages of Alzheimer’s through functional magnetic resonance imaging.
Researchers have designed a wearable device that monitors sweat for biomarkers that could signal flare-ups of inflammatory bowel disease (IBD).
Researchers at King’s College London, Massachusetts General Hospital and health science company ZOE have developed an AI diagnostic that can predict whether someone is likely to have COVID-19 based on their symptoms.
A machine learning method discovered a clue in people’s language predictive of the emergence of psychosis — the frequent use of words associated with sound.
VR can identify early Alzheimer’s disease more accurately than ‘gold standard’ cognitive tests currently in use, suggests new research from the University of Cambridge.
By speaking the brain’s language, the material is a portal between electronics and the brain.
Researchers are working on a smart insole that flags changes in a patient’s gait, activity level and balance, as well as monitors for the localized increase in heat that can reveal a building infection before the human eye can spot it.
Researchers are developing an app and wearable technology to enable pregnant women to use a smartphone to detect whether they have a condition that could lead to serious health complications for them or their unborn child.