Academic researchers in the U.K. have completed a systematic review of 62 representative studies on the use of AI for COVID-19 diagnostics and prognostics on X-rays and CT scans. Their findings may strike some as a setback.  

Researchers have demonstrated that deep learning models can help neurologists interpret epileptic episodes during and between seizures from relatively few scalp electroencephalography (EEG) readings.

Researchers have developed an AI-based system that can direct the administering of iron and other red-blood-cell stimulators nearly as well as experienced physicians.

The advance represents the first cancer-care pathway offering an automatically combined analysis of morphological, molecular and histological data. 

Researchers in Italy have demonstrated a no-cost, AI-based technique for detecting the presence of previously undiagnosed abnormalities in blood sugar stability.

If verified in additional trials, the advance will facilitate care planning much earlier than the current average age of diagnosis, 4 years old.

AI can be taught to flag possible skin cancers on photos taken with smartphone cameras—and the images can be ordinary “people shots” rather than closeups of suspicious lesions.

The tool makes the call based on factors readily available to busy clinicians, respecting their workflows while helping patients and families decide whether moving to access a stepped-up care setting would fit well with their aims and values.