Artificial intelligence is already powering your Google searches, your Netflix recommendations, and your smartphone's virtual assistant. It is playing humans at complex, intuitive games like Go, and it is beating them. Now, researchers say, they want AI to power your doctor's diagnoses, your drug prescriptions, and your smartphone's virtual psychologist. They want AI to perform tasks that radiologists do, and at least match them. Machine learning has made tremendous strides in the last decade, becoming one of the fastest-growing, most-hyped areas of computer science.
Make room, stethoscope and otoscope. Artificial intelligence (AI) applications are increasingly among the physician's standard instruments,experts at the University of Toronto say. "With electronic records, you can use text algorithms to read a patient's history, review their genetic predispositions, and correlate the information to make predictions," says Dr. Frank Rudzicz. Rudicz is one of five experts exploring the issues of privacy, accuracy and accountability at The Robot Will See You Now – the Revolution in Artificial Intelligence and Medicine at U of T on April 5. A research scientist with the Toronto Rehab Institute and an assistant professor (status only) in the department of computer science at the University of Toronto, Rudzicz is also a project lead within a federally funded national research network in technology and aging known as AGE-WELL NCE.
Experts in computer science and medicine explored issues related to the ethical use of artificial intelligence in medicine during a panel discussion at the University of Toronto. The University of Toronto (U of T) hosted a panel discussion Tuesday on the ethical use of artificial intelligence (AI) in medicine. Integrating AI successfully into the nuanced setting of patient and doctor interaction and communication creates intriguing challenges for researchers. Natural language expert Graeme Hirst says a medical AI would have to talk to patients in language used in the real world and deal with all issues of complex conversation and health communication.
Winterlight Labs, a spinoff from the University of Toronto, is using natural language processing (NLP) and machine learning to identify people with Alzheimer's disease (AD) and other forms of dementia based on patterns in their recorded speech. The World Health Organization estimates that 47.5 million people in the world have dementia, which is defined as a chronic or persistent disorder of the brain marked by lapses in memory, personality changes, and impaired reasoning. In developed countries, AD is one of the most costly of all diseases to treat. Every year in the United States, 236,000 people are diagnosed with AD. There are an additional 100,000 healthy individuals over the age of 60 who seek AD screening.
SAN JOSE, CA--(Marketwired - Apr 5, 2016) - GPU Technology Conference -- NVIDIA (NASDAQ: NVDA) today announced that it is a founding technology partner of the MGH Clinical Data Science Center, which aims to advance healthcare by applying the latest artificial intelligence techniques to improve the detection, diagnosis, treatment and management of diseases. Massachusetts General Hospital -- which conducts the largest hospital-based research program in the United States, and is the top-ranked hospital on this year's US News and World Report "Best Hospitals" list -- recently established the MGH Clinical Data Science Center in Boston. The center will train a deep neural network using Mass General's vast stores of phenotypic, genetics and imaging data. The hospital has a database containing some 10 billion medical images. To process this massive amount of data, the center will deploy the NVIDIA DGX-1 -- a server designed for AI applications, launched earlier today at the GPU Technology Conference -- and deep learning algorithms created by NVIDIA engineers and Mass General data scientists.