Tech & Health

Project aims to improve ear disease diagnoses with objective machine learning techniques

A new project, funded by the National Institutes of Health (NIH), National Institute on Deafness and Other Communication Disorders (NIDCD) and led by Aaron Moberly, MD, and Metin Gurcan, PhD, professor and director of the Center for Biomedical Informatics and the Clinical Image Analysis Lab at Wake Forest University School of Medicine, aims to develop machine learning applications to analyze eardrum videos collected with a digital otoscope.

Neural networks probe proteins

A machine learning method based on neural networks outperformed a mutational scanning model at identifying disease-causing mutations in an Alzheimer’s disease protein, suggesting the method could be useful for facilitating therapeutic design.

Malin receives a Vanderbilt distinguished service award

Bradley Malin, PhD, has received one of Vanderbilt University’s top honors, the Alexander Heard Distinguished Service Professor Award.

COVID on Twitter: town vs. country

A natural language processing analysis of 407 million tweets from May 2020 to January 2022 captures the rural-urban divide regarding COVID-19.

The problem with the problem list

Algorithms to infer missing problems and suggest that they be added to electronic health records improved problem list completeness, with benefits for clinical care, patient comprehension of health conditions and population health.

The study could suggest ways to promote the transport of phospholipids and cholesterol out of macrophages, immune system cells that play key roles in all stages of atherosclerosis development.

Reminders for clinicians improve prescribing for high cholesterol

A Vanderbilt study found that automated targeted reminders for clinicians helped increase prescribing of high intensity statins for patients with various atherosclerotic cardiovascular disease diagnoses, including coronary or peripheral artery disease and ischemic stroke.

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