Large language models (LLMs) performed poorly in navigating early clinical diagnostic uncertainty
1. Rao and colleagues evaluated the clinical reasoning performance of 21 off-the-shelf LLMs across 29 standardized clinical vignettes. 2. While...
Smartphone-based digital ruler achieved high diagnostic performance for strabismus screening
1. Wang and colleagues developed a system that uses deep learning algorithms to analyze cover tests recorded by suspected strabismus...
Deep-learning models displayed expert-level accuracy in detecting epileptiform discharges on electroencephalogram (EEG) recordings
1. Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model...
Ambient artificial intelligence effectively reduced work exhaustion among healthcare providers
1. Afshar and colleagues evaluated an artificial intelligence (AI) scribe’s ability to produce clinical documentation and alleviate work exhaustion. 2....
Large language models (LLMs) substantially improved patient comprehension of discharge summaries
1. Kumar and colleagues assessed LLM’s ability to translate discharge summary notes into plain language to improve patient comprehension. 2....
Machine learning models effectively screened for Parkinson’s disease using smile videos
1. Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The...
Artificial intelligence (AI) may reduce cognitive load for sonographers in fetal ultrasound scans without affecting diagnostic performance
1. Day and colleagues randomized sonographers to scan pregnant participants with AI assistance or the standard method for congenital heart...
Juror perception of radiologist liability can be affected by artificial intelligence (AI) use in diagnosis
1. Bernstein and colleagues evaluated potential jurors’ perception of culpability of a radiologist in a hypothetical false-negative diagnosis malpractice case....
Natural language processing (NLP) model sped up patient message management in the electronic health record (EHR)
1. Anderson and colleagues evaluated clinical staff’s response time to patient-sent messages with NLP labelling against that of staff without...
Machine learning models diagnose celiac disease at similar performance levels to pathologists
1. Jaeckle and colleagues assessed the performance of machine learning models to diagnose celiac disease based on duodenal biopsies. 2....
