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Study found that use of an AI-driven gamified mobile app integrating home blood pressure monitoring significantly improved blood pressure control compared to usual care in hypertensive patients.
This study assesses the perceptual realism of synthetic laryngeal images created using StyleGAN3, revealing high ambiguity between real and synthetic frames and highlighting efficient training durations for realistic image generation.
A novel AI-driven risk prediction model for ovarian cancer demonstrates high accuracy and potential to improve early detection in screening settings.
A novel deep learning algorithm accurately detects moderate or greater aortic stenosis using AI-guided focused cardiac ultrasound acquired by novice operators, presenting a scalable solution to expand screening accessibility.
A validated deep learning model accurately detects surgical site infections from wound images, offering a promising telemedicine tool for early postoperative monitoring and timely clinical intervention.
This study examines the increased use of AI-associated writing vocabulary in ophthalmology articles, revealing faster adoption by non-native English authors without changes in publication frequency or journal quality.
This study introduces a validated machine learning tool providing personalized probability scores to improve cochlear implant candidacy screening, surpassing traditional rules by enabling tailored patient counseling and identifying borderli
Introduction: The Collision of AI Hype and Life Sciences Compliance The rapid adoption of artificial intelligence has officially collided with strict
The PREVUE-VALVE Study demonstrates that AI-ECG models developed in hospital settings show reduced diagnostic accuracy when applied to community populations with lower disease prevalence and milder structural heart disease, underscoring the
Machine learning models can effectively predict major 30-day complications following glossectomy for tongue cancer, improving individualized risk assessment over traditional methods.
A machine learning model using simple clinical tests within 72 hours poststroke accurately predicts 6-month upper-limb motor outcomes, aiding rehabilitation planning.
The SAVE-O2 AI trial demonstrates autonomous oxygen titration significantly improves normoxemia maintenance and reduces hypoxemia duration compared to manual methods in hospitalized acutely ill adults.
This study evaluates four commercially available AI systems for diabetic retinopathy screening in Tanzania, demonstrating high sensitivity for referable and proliferative DR and highlighting considerations for implementation in low-resource
This study explores the potential of an AI-powered ECG tool to monitor left ventricular systolic dysfunction in hypertrophic cardiomyopathy patients treated with mavacamten, offering a less burdensome alternative to frequent echocardiograms
Highlight Deep learning applied to 12-lead ECG signals enables estimation of 10-year ischemic stroke risk with moderate discrimination and good calibr
Highlight This unprecedented large-scale multinational study developed a semisupervised contrastive machine learning framework that generates a global
A pilot study demonstrates that ChatGPT-4 can feasibly collect accurate and satisfactory medical histories from pediatric emergency patients, streamlining triage and reducing documentation burden.
This article explores AMBUSH-AI, a novel AI-driven system utilizing ultrasound modalities to accurately predict burn wound depth, improving diagnostic accuracy beyond current clinical standards and potentially guiding optimal surgical decis
A prospective multicenter study demonstrates that AI-driven virtual native enhancement (VNE) MRI can accurately detect and quantify myocardial scars without contrast agents, potentially reducing the need for gadolinium-based imaging in clin
Recent research demonstrates that machine learning algorithms can accurately predict patient-reported outcomes one year after breast reconstruction, potentially enhancing shared decision-making and individualized care planning.
Open language-specific specialty feeds and department pages.