AI-powered smartphone app diagnoses ear infections

An image of the tympanic membrane. [Image courtesy of UPMC]

Physician-scientists at UPMC and the University of Pittsburgh found a way to use AI to accurately diagnose ear infections.

The AI-powered smartphone app that diagnoses acute otitis media (AOM) could help decrease unnecessary antibiotic use in young children. Researchers published their outcomes in JAMA Pediatrics.

AOM commonly has antibiotics prescribed to treat it, but can prove difficult to discern from other ear conditions without intensive training. This AI tool makes a diagnosis by assessing a short video of the eardrum captured by an otoscope connected to a smartphone camera. The researchers say this offers a simple and effective solution with potentially more accuracy than trained clinicians’ diagnoses.

“Acute otitis media is often incorrectly diagnosed,” said senior author Dr. Alejandro Hoberma, pro…

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Machine learning model flags patients with high risk of surgical complications

Improving the health of high-risk patients before their surgeries can lower mortality rates and cut healthcare costs. [Image by Gorodenkoff via Adobe Stock]

A newly developed machine learning model for surgical patients is automatically flagging those at high risk of complications to improve their odds of survival and reduce healthcare system costs.

Each day, the software reviews electronic medical records for patients scheduled for surgery and identifies those who might benefit from individualized coordinated care or prehabilitation to improve surgical results.

Researchers and physicians at the University of Pittsburgh and University of Pittsburgh Medical Center (UPMC) trained their algorithm on medical records for more than 1.2 million surgical patients. To help predict whether patients might suffer from complications after surgery, they focused the model on deaths from strokes, heart attacks and other…

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