Also called personalized medicine, this evolving field makes use of an individual’s genes, lifestyle, environment and other factors to identify unique disease risks and guide treatment decision-making.
Cynthia Rudin, PhD, is a highly regarded computer scientist who’s been eyeing the advance of artificial intelligence into society with equal parts enthusiasm and concern.
By now it’s a difficult-to-dispute likelihood: AI won’t replace doctors making diagnoses, but doctors who use AI will displace doctors who don’t use AI. The hypothesis gets a fresh airing out from the vantage point of the general public.
A new machine learning-based system, detailed in the journal Frontiers in Neurology, screens children for fetal alcohol spectrum disorder (FASD) in a quick and more cost-efficient way. The system was developed by researchers at the University of Southern California, Queen’s University in Ontario and Duke University, and will be accessible to children in more remote areas of the globe.
An AI-based sepsis screening tool could better help physicians find patients most at risk of developing the illness after it outperformed other traditional screening methods, according to a study published in the Annals of Emergency Medicine.
Multinational investment holding conglomerate Tencent is working with the Shanghai Cancer Center to establish an AI-based, big data laboratory to streamline the cancer treatment process, according to a report by Shine, a digital news organization under Shanghai Daily.
Researchers have developed a machine learning system that predicts the severity of arthritis in a pediatric population, allowing for treatment to be personalized. Findings of their research were published inPLOS Medicine.
As the number of diabetes cases continues to rise in India, Google and Verily, the life sciences research organization under Alphabet, have a solution to better screen for the disease and associated eye diseases.
Researchers at the University of Alberta have developed a new AI-based software––Ensemble Algorithm with Multiple Parcellations for Schizophrenia Prediction, or EMPaSchiz––that will allow physicians to identify schizophrenia in fMRI scans with 87 percent accuracy. Their research was published inNJP Schizophrenia.
Dana Solutions, a California-based AI company, is partnering with the FDA’s Center for Drug Evaluation and Research to improve the drug development process by using AI, the company announced Feb. 25.
A new machine learning model allows for physicians to determine whether atypical ductal hyperplasia (ADH) could upgrade to cancer, according to new research published inJCO Clinical Cancer Informatics. The model can identify 98 percent of all malignant cases prior to surgery, while sparing 16 percent of women from unnecessary surgeries.
U.S. health systems are increasingly leveraging digital health to conduct their operations, but how health systems are using digital health in their strategies can vary widely.
When human counselors are unavailable to provide work-based wellness coaching, robots can substitute—as long as the workers are comfortable with emerging technologies and the machines aren’t overly humanlike.
A vendor that supplies EHR software to public health agencies is partnering with a health-tech startup in the cloud-communications space to equip state and local governments for managing their response to the COVID-19 crisis.
