CHANDIGARH: Twitter and other social media websites, meant for the medical community, will soon be used extensively as a part of teaching artificial intelligence at the PGI. Artificial intelligence (AI) can be used specifically in the radiology to predict the onset of any disease in advance. As per the doctors, the technique is necessary for the health care system. "We are having collaborations with some of the IITs for this. But there is no full time course and none from the faculty knows about the AI. We will soon propose to our director to start the course here," said Prof M S Sandhu, head, department of radiodiagnosis, PGI.

A team of Waterloo researchers found that applying artificial intelligence to the right combination of data retrieved from wearable technology may detect whether your health is failing. The study, which involved researchers from Waterloo's Faculties of Applied Health Sciences and Engineering, found that the data from wearable sensors and artificial intelligence that assesses changes in aerobic responses could one day predict whether a person is experiencing the onset of a respiratory or cardiovascular disease. "The onset of a lot of chronic diseases, including type 2 diabetes and chronic obstructive pulmonary disease, has a direct impact on our aerobic fitness," said Thomas Beltrame, who led the research while at the University of Waterloo, and is now at the Institute of Computing in University of Campinas in Brazil. "In the near future, we believe it will be possible to continuously check your health, even before you realize that you need medical help." The study monitored active, healthy men in their twenties who wore a shirt for four days that incorporated sensors for heart rate, breathing and acceleration.

Artificial Intelligence Used to Predict Onset of Alzheimer's

The classifiers can be represented as discrimination maps, where a red color indicates that the intensity at that location contributes to the likelihood of the images belonging to the more advanced stage, and a blue color to the likelihood of belonging to the less advanced stage. Weights are shown inside the mask that resulted in the highest accuracies for each classification: A: Alzheimer's disease (AD) vs. subjective cognitive decline (SCD); B: AD vs. mild cognitive impairment (MCI); C: MCI vs. SCD. At the VU University Medical Center Amsterdam researchers are harnessing the power of artificial intelligence to be able to detect early signs of Alzheimer's on MRI scans. The parenchyma exhibits small incremental changes on the scan as the disease develops, but these are difficult to spot in new patients. Only once the disease is at a later stage clinicians are able to identify the disease from the scans, but by then it's usually already exhibiting well known symptoms.