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Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.

JAMA cardiology
IMPORTANCE: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality.

Application of improved glomerular filtration rate estimation by a neural network model in patients with neurogenic lower urinary tract dysfunction.

Clinical nephrology
BACKGROUND: Previous studies have indicated that creatinine (Cr)-based glomerular filtration rate (GFR) estimating equations - including the new Chronic Kidney Disease Epidemiology creatinine (CKD-EPI) equation without race and the estimated glomerul...

A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression.

JAMA cardiology
IMPORTANCE: Aortic stenosis (AS) is a major public health challenge with a growing therapeutic landscape, but current biomarkers do not inform personalized screening and follow-up. A video-based artificial intelligence (AI) biomarker (Digital AS Seve...

Results From a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence With Conditional Economic Incentives Among Young Adults With HIV.

Journal of acquired immune deficiency syndromes (1999)
BACKGROUND: Despite improvements in antiretroviral therapy (ART) availability, suboptimal adherence is common among youth with HIV (YWH) and can increase drug resistance and poor clinical outcomes. Our study examined an innovative mobile app-based in...

Innovative utilization of ultra-wide field fundus images and deep learning algorithms for screening high-risk posterior polar cataract.

Journal of cataract and refractive surgery
PURPOSE: To test a cataract shadow projection theory and validate it by developing a deep learning algorithm that enables automatic and stable posterior polar cataract (PPC) screening using fundus images.

Toward personalized care for insomnia in the US Army: a machine learning model to predict response to cognitive behavioral therapy for insomnia.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: The standard of care for military personnel with insomnia is cognitive behavioral therapy for insomnia (CBT-I). However, only a minority seeking insomnia treatment receive CBT-I, and little reliable guidance exists to identify those...

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm.

Diabetes technology & therapeutics
Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encod...

AUTOMATED DETECTION OF VITRITIS USING ULTRAWIDE-FIELD FUNDUS PHOTOGRAPHS AND DEEP LEARNING.

Retina (Philadelphia, Pa.)
BACKGROUND/PURPOSE: Evaluate the performance of a deep learning algorithm for the automated detection and grading of vitritis on ultrawide-field imaging.

Deep learning for automatic volumetric segmentation of left ventricular myocardium and ischaemic scar from multi-slice late gadolinium enhancement cardiovascular magnetic resonance.

European heart journal. Cardiovascular Imaging
AIMS: This study details application of deep learning for automatic volumetric segmentation of left ventricular (LV) myocardium and scar and automated quantification of myocardial ischaemic scar burden from late gadolinium enhancement cardiovascular ...