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.
AI systems can detect breast cancer just as well as radiologists, according to a study published March 5 in the Journal of the National Cancer Institute.
Amazon has extended a grant valued at $2 million to Harvard Medical School so the medical giant can experiment with machine learning and AI to streamline their clinical workflow, Bloomberg reported March 4.
Researchers from the Icahn School of Medicine at Mount Sinai have developed an AI platform that’s reportedly capable of detecting a range of neurodegenerative diseases in human brain tissue samples, according to a study published in the February issue of Laboratory Investigation.
Using big data and AI-driven prediction models can be clinically useful, but it’s also important to learn about that data and the processes involved in collecting it, according to work published in JAMA Psychiatry.
Researchers at the Children’s Hospital of Philadelphia (CHOP) developed machine learning models that can detect the presence of sepsis in infants, hours before physicians. Findings from the study were published inPLOS One.
Though AI systems have shown promise for detecting skin cancer, more work is needed before they can be utilized in “real world” applications, according to researchers at the 2019 American Academy of Dermatology annual meeting in Washington, D.C.
OOVA, a Mount Sinai Health System spinout and diagnostic device company, is piloting an AI-based fertility tool that measures and monitors the concentrations of luteinizing hormone and progesterone—two key fertility hormones. The program is being piloted in collaboration with Thorne Research.
Researchers at the University of California, San Francisco found Google Translate, Google’s AI-based app, can help non-English speaking patients and their providers. However, it's not perfect, according to research published inJAMA Internal Medicine.
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.
