More than one-quarter of the U.S. adult population has Gastroesophageal Reflux Disease, or GERD, and the condition saddles as many as 20% of its sufferers with Barrett’s esophagus. The latter is a serious risk factor for esophageal cancer.

A convolutional neural network has proven adept at predicting the spread of colorectal cancer to the lymph nodes using automated analysis of histology slides.

Harvard researchers have demonstrated a web-based program that allows cognitively normal individuals to screen themselves, unsupervised, for the type of memory decline that may signal encroaching Alzheimer’s disease.

Cambridge University researchers propose using the technique to predict individuals’ health issues over time and intervene early with personalized preventive care.

Is the world ready for AI-equipped smartphones that can reliably identify or rule out COVID-19 based on audio data from coughing and speaking?

In cancer research settings, AI has shown strong capabilities for predicting risk, recurrence and survivability over the past 10-plus years. Yet real-world cancer mortality remains largely unchanged to the present day. Why is that?

AI should not be used to predict the course of clinical depression if all it has to work with are new patients’ medical records of past diagnoses, medications, encounters and patient-reported outcomes.

AI and machine learning are adept at selecting good candidates for total joint arthroplasty and predicting which patients will and won’t experience post-op complications.