Chest pain is one of the most common reasons patients visit the emergency department (ED), but relatively few are eventually diagnosed with myocardial infarction (MI). New research found a machine learning algorithm can predict MI with 94 percent accuracy.

The healthcare industry is poised to see a 40 percent increase in the artificial intelligence (AI) market in the coming years—and, despite heavy regulations, the industry continues to improve utilization.

Researchers from the University of Southern California Viterbi School of Engineering have developed an algorithm capable of slowing the spread of infectious diseases while accounting for limited resources and population dynamics. Findings are published in the AAAI Conference on Artificial Intelligence.

A Baltimore-based company is utilizing the power of artificial intelligence (AI) and deep learning to advance drug discovery, biomarker development and aging research.

Researchers at the University of California, San Francisco and digital health startup Cardiogram have found the Apple Watch capable of detecting patients with diabetes with 85 percent accuracy.

A novel deep learning algorithm could hold the key to proactive palliative care—and predict patient deaths, according to a paper published by the Stanford University School of Medicine in California.

As artificial intelligence (AI) becomes more advanced and commonplace in medicine, patients are excited about the possibilities the technology could bring to care, according to a report released by Syneos Health Communications.

The healthcare technology startup Medopad, which developed a tool for clinicians to track the vital signs, has used large populations from China to improve the predictive analytics of their artificial intelligence (AI).