Artificial Intelligence

ChatGPT correctly and satisfactorily answered nine out of 10 frequently asked questions about glaucoma concerning general information, diagnosis, treatment and prevention, according to an analysis published in Journal of Glaucoma.

An AI algorithm had high discriminative ability in identifying pulmonary hypertension-likely patients from control patients at and before diagnosis using electrocardiogram data, according to study results.

In this Healio Video Perspective, Cynthia Matossian, MD, FACS, and David Evans, PhD, MBA, provide insight into how ophthalmology practices can harness the abilities of AI tools such as ChatGPT.

Health care providers know of the broad potential AI offers for reducing burnout, but which products are actually available for use can be difficult to ascertain, especially considering electronic health record system compatibility.

A low-cost, battery-powered ultrasonography probe with integrated AI for image interpretation reliably measured gestational age compared with standard ultrasound, providing a possible option for low-resource settings, diagnostic data show.

With the use of AI-enabled quantitative coronary plaque analysis, researchers developed nomograms designed to improve risk stratification of patients who may be at risk for atherosclerosis.

Explanations of echocardiography findings written using ChatGPT may be suitable to educate patients about their health status and reduce physician workload, according to data published in JACC: Cardiovascular Imaging.

Autonomous AI exhibited “noninferior accuracy” for optical diagnosis of diminutive colorectal polyps vs. AI-assisted endoscopists, yet surpassed endoscopist accuracy in later pathology-based surveillance intervals, according to researchers.

Chatbots use of more positive and subjective language produced more empathetic responses to patient questions submitted through EHR prompts compared with those of primary care physicians, according to results of a randomized study.

In this episode, host Shikha Jain, MD, speaks with Shyam Natarajan, PhD, about machine learning in cancer research and testing, using technological innovation to address disparities in health care trials and more.