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A VITAL-AF trial analysis reveals that combining ECG-based artificial intelligence with clinical risk scores significantly improves atrial fibrillation screening efficiency. The study demonstrates that high-risk individuals benefit most fro
Researchers have developed an AI-powered framework that uncovers a non-linear relationship between tumor-stroma ratio and mortality in hepatocellular carcinoma, using a novel token-guided multimodal fusion approach to improve prognostic acc
Researchers developed and validated ADAPT-CEC, an artificial intelligence algorithm that can adjudicate cardiovascular events across different trial definitions. A hybrid approach combining AI with selective human review achieved 95.6% accu
A large-scale multicenter RCT investigating AI-assisted gastric neoplasm detection found no significant improvement in pathologically confirmed detection rates but demonstrated significant reductions in procedural blind spots and benefits f
This review evaluates the breakthrough ECG2HF model, a publicly available AI tool that outperforms standard clinical scores in predicting 10-year heart failure risk using 12-lead ECG waveforms.
A multicenter study in JAMA Ophthalmology introduces a deep learning model using domain-shift technology to accurately detect macular diseases across different OCT hardware vendors, achieving high negative predictive value and establishing
The MASAI trial demonstrates that AI-supported mammography screening achieves higher sensitivity and non-inferior interval cancer rates compared to standard double reading, while maintaining specificity and significantly reducing radiologis
The TRICORDER trial demonstrates that while AI stethoscopes are capable of detecting heart failure, atrial fibrillation, and valvular disease, their real-world implementation in UK primary care did not yield a statistically significant incr
A crossover study involving 30 ophthalmologists and trainees reveals that while Claude-3.5-Sonnet collaboration improves diagnostic accuracy in complex cases, it also increases confidence in incorrect decisions and fails to reach the perfor
This multi-institutional study validates Neuropath-AI, a deep-learning system that predicts CNS tumor types by inferring molecular features from histopathology slides. Achieving 80% top-1 accuracy in high-confidence samples, the model offer
A single-center study demonstrates that an AI pipeline for CT-based lymph node segmentation and extranodal extension classification significantly improves prognostic accuracy for HPV-positive oropharyngeal cancer compared to traditional rad
A longitudinal study published in NEJM AI evaluates seven generative AI chatbots for alcohol misuse support, finding that while they excel in empathy and non-judgmental language, they frequently provide low-quality or inaccurate medical inf
This independent validation study confirms that AI-enhanced ECG models effectively detect left ventricular systolic dysfunction across diverse populations, achieving AUROCs up to 0.93. However, significant barriers remain regarding model tr
A randomized multimethod study reveals that while AI clinical decision support systems for antibiotic switching are well-received, their primary influence is reinforcing conservative prescribing. The study underscores that usability and cli
A validated multimodal AI model using digital pathology and clinical data significantly improves risk stratification for prostate cancer patients with biochemical recurrence, identifying those who derive the greatest benefit from salvage ho
A deep learning analysis of the PanaMa trial reveals that the benefit of adding panitumumab to maintenance therapy for RAS wild-type mCRC is significantly higher in patients with a high muscle-bone ratio, suggesting a new AI-driven approach
The PECTUS-AI study demonstrates that AI-based identification of thin-cap fibroatheromas using OCT provides superior prognostic value for cardiovascular events compared to manual analysis, particularly when assessing the entire imaged coron
A groundbreaking study utilizing an AI classifier demonstrates that ARDS inflammatory phenotypes are dynamic and dictate corticosteroid efficacy. While hyperinflammatory patients benefit from steroids, hypoinflammatory patients face increas
AI-driven analysis of routine chest CTs reveals that coronary artery calcium is highly prevalent and strongly predictive of MACE and mortality in patients with IMIDs, identifying a critical treatment gap in this high-risk population.
A large-scale prospective study across England’s NHS reveals that AI imaging software significantly boosts endovascular thrombectomy rates for acute stroke patients. Implementation was associated with a 100% relative increase in treat