Diagnostics

Physician burnout is undoubtedly a serious issue in the medical profession—and it often stems from physicians’ EHR use, which, by some estimates, accounts for up to six hours of their daily work load. That's six hours is not dedicated to visiting with patients, a new article in Forbes suggests.

More than 300 companies, universities and organizations are investing more than $260 million to support 16 new centers for doctoral training in AI in the United Kingdom.

With alcohol misuse playing a role in more than 25 percent of trauma cases, Loyola University researchers have developed a method that uses AI to predict the signs of alcohol misuse in these patients. The method could serve as an affordable option for trauma centers.

A new AI method that allows physicians to identify and predict the development of symptoms in post-chemotherapy patients is being tested by researchers from the University of Surrey and the University of California. Findings of the study were published in Scientific Reports.

Researchers from the Imperial College London and the University of Melbourne created a new AI algorithm that is four times more accurate in predicting survival rates among ovarian cancer patients. The tool was also able to determine the most effective treatment for patients who exhibit ovarian cancer. Research findings were published in Nature Communications.

Flagler Hospital, a 335-bed community hospital based in St. Augustine, Florida, is projected to save more than $20 million after AI technology helped it reduce costs, average length of stay and readmissions for pneumonia patients. 

Medical device company Sight Diagnostics has raised $27.8 million in funding to expand its system that uses AI to analyze blood tests, according to a report by VentureBeat.

Health technology company Cerner is now offering an AI workflow tool that aims to temper physician burnout, the company announced during the HIMSS conference in Orlando.

Researchers in China have developed an AI-based natural language processing algorithm which processes free text from physician notes in electronic health records (EHRs) to predict common ailments in a pediatric population. The algorithm outperformed junior physicians in diagnosing some illnesses.

Researchers at the University of Lethbridge used AI to analyze blood biochemistry in smokers—and found smoking makes people biologically older. Results of the study were published in Scientific Reports.

Machine learning models could be used to help improve the prediction ability of emergency room (ER) triage methods, after a JAMA study showed the technology was better at making clinical predictions than traditional approaches.

A patent application filed by Google indicates that the company is looking to develop an electronic health records (EHR) system that uses AI to predict a patient’s future medical events.