Deep Learning

LAS VEGAS — The use of AI deep learning can help forecast acute dialysis needs and enhance staffing efficiency in hospitals, according to a speaker.

OCT angiography alone demonstrated superior sensitivity in detecting glaucomatous changes in the optic disc and macula compared with OCT and OCT angiography combined, according to a study published in Clinical Ophthalmology.

The accuracy of an artificial neural network in identifying COPD and Global Initiative for Chronic Obstructive Lung Disease, or GOLD, stage was similar with use of single-phase CT or inspiratory-expiratory CT, according to study results.

BOSTON — A multimodal fusion model outperformed transthoracic echocardiography in identifying pulmonary hypertension, according to a study presented at the CHEST Annual Meeting.

A deep learning system achieved an accuracy of more than 90% in distinguishing arteritic from nonarteritic anterior ischemic optic neuropathy using only color fundus images, according to a study published in JAMA Ophthalmology.

Polysomnography is the current gold standard in sleep testing, but a new method has achieved similar performance in sleep stage scoring via an electrocardiography-based deep learning neural network, according to a press release.

Artificial intelligence may have a role in the early detection of rheumatic heart disease using mitral regurgitation jet analysis, according to study findings published in the Journal of the American Heart Association.

A novel deep learning algorithm applied to a single preoperative ECG improved risk prediction for death after cardiac surgery and other inpatient procedures for a large cohort, researchers reported.

The rise of deep learning and artificial intelligence in retinal disease, and all of ophthalmology, is proceeding at a staggering pace.

Published results showed a smartphone app-based validated deep learning model was able to diagnose and monitor adolescent idiopathic scoliosis at minimal cost with no additional radiation.