Diagnostics

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.

With AI becoming more prevalent in medical practice, Dhruv Khullar, MD, a physician at New York-Presbyterian Hospital and assistant professor at Weill Cornell Medicine, detailed how AI is a contributor to the worsening of health disparities in a New York Times opinion piece.

Researchers at the University of Southern California Viterbi School of Engineering have utilized machine learning to detect clusters of potential biomarkers of Alzheimer’s disease. This will allow for earlier diagnosis and could potentially lead to non-invasive methods of tracking the progression of the disease in impacted patients. Findings were published in the journal Frontiers in Aging NeuroScience.

Using an AI-based method, researchers at Cardiff University in Cardiff, Wales, developed a clinical prediction model, according to a study published in PLOS One. The model showed it can provide an accurate and reliable prognosis for patients with cardiovascular disease when compared to traditional methods.

Scientists at the University of Cambridge are developing a machine learning tool to better predict individuals’ long-term risk of developing cardiovascular disease (CVD)—specifically, heart attack or stroke.