Stanford researchers have demonstrated a way to remotely diagnose autism in children in Bangladesh.

Using deep learning to tease out factors indicative of age-related variability in the way toddlers gaze at visual stimuli, researchers at the University of Minnesota have shown that the technology can accurately distinguish 18-month-olds from 30-month-olds.

Working with SRI International, the California tech lab that gave the world Siri, mental-health specialists at NYU Langone have developed an AI-based tool that uses voice analysis to diagnose posttraumatic stress disorder—potentially via telemedicine.

A deep-learning algorithm trained entirely on open-source images has outperformed 136 of 157 dermatologists at classifying melanoma, according to a study running in the May edition of the European Journal of Cancer.

Researchers from the National Institutes of Health, Radiological Society of North America, American College of Radiology and Academy for Radiology and Biomedical Imaging Research have published what they’re calling a “roadmap for AI” in medical imaging—a framework for accelerating foundational research in the field.

The FDA granted GE Healthcare’s Deep Learning Image Reconstruction (DLIR) platform 501(k) clearance April 18, marking the first time the agency has approved a deep learning-based CT image reconstruction technology.

The field of AI is currently at the center of a far-reaching diversity crisis, according to a report issued this April.

Months-old health technology startup Theator closed a $3 million seed round April 18, providing the company with the cash flow it needs to power its AI-enabled surgical performance platform.

Michigan-based startup HistoSonics raised $54 million in its Series C funding round to support the noninvasive Robotically Assisted Sonic Therapy (RAST) platform, an AI solution that combines advanced robotics and imaging to destroy unwanted tissue.