A three-layer artificial intelligence ensemble accurately forecasts post-traumatic stress disorder risk from emergency department trauma narratives, matching expert clinical evaluations.
A blinded study in BMC Urology found no significant difference in quality between three LLM systems and two urologists for ...
A review in Cell Division evaluates AI and machine learning models for pancreatic cancer diagnosis, highlighting their high reliability in ...
A mini-review proposes an EHR-integrated framework combining quantitative ocular biometrics and automated risk stratification to improve perioperative decision-making in ophthalmology.
Researchers propose a causal governance framework and multi-agent architecture to distinguish clinically justified contextual differences from harmful algorithmic bias in ...
A scientific review published in BMC Artificial Intelligence evaluates how artificial intelligence, robotics, and natural language processing advance telemedicine and ...
A systematic review of 35 studies demonstrates that machine learning models analyzing structured clinical, imaging, and demographic data achieve diagnostic ...
A systematic review and meta-analysis reveals that artificial intelligence decision support significantly enhances fracture detection sensitivity for clinicians, delivering the ...
A new machine learning model developed by researchers predicts the risk of recurrence in patients with borderline ovarian tumors undergoing ...
A commentary in npj Digital Medicine outlines a framework for resolving divergence between clinical judgment and artificial intelligence through parallel ...
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