Tag: Clinical decision support

Herbal medicines are no longer fringe therapy. Across hospitals in Southeast Asia, patients routinely combine conventional prescription drugs with herbal ...

A two-step machine learning framework trained on more than 23,000 clinical records from Indian newborn units identified 84.9 percent of ...

Researchers have developed a Michigan-style genetic fuzzy system that turns sparse multiple sclerosis records into transparent forecasts of disability progression, ...

A new evidence-guided framework called E-MDD combines deep EEG representations, neurophysiological biomarkers, and a constrained large language model to detect ...

Researchers have developed a deep reinforcement learning framework that generates synthetic patient data and explicitly avoids high-risk clinical states, outperforming ...

The JAMA Network has announced JAMA AI, a new peer-reviewed journal launching in early 2027 that will publish clinical research ...

Researchers trained AI models on short Spanish first-contact clinical notes and found the algorithms detected suicidal behavior more accurately than ...

A systematic review of 91 studies shows AI-based medication recognition advancing rapidly through detection, OCR, and few-shot learning, while external ...

A new Journal of Medical Systems commentary argues that laboratory-aware AI checklists stop at the model, leaving semantic stability after ...

An XGBoost artificial intelligence model trained on Swedish neurointensive care data has successfully predicted dangerous intracranial pressure surges in traumatic ...

A new Journal of Medical Systems commentary proposes a task-level oversight-margin framework to quantify when human supervision of cardiovascular artificial ...

A new scoping review maps how artificial intelligence is being tested across emergency care and disaster response, and finds that ...

A retrospective case-control study found that an electronic health record based neonatal sepsis screening tool achieved 81 percent sensitivity and ...

A new risk-calibrated tabular Transformer achieves state-of-the-art Alzheimer's disease staging while calibrating its confidence and abstaining on uncertain cases.

A new data-driven framework called STREAM models ICU patients as trajectories through a multidimensional physiological space, identifying state outliers whose ...

A scoping review finds only three studies of artificial intelligence for assessing fever in returning travellers, all promising in controlled ...

Chinese researchers have developed and externally validated a prediction model combining PSA, tumor stage, biopsy grade, and the neutrophil-to-lymphocyte ratio ...

A schema-enforced large language model framework achieved 94 percent reproducibility across simulated sarcoma tumor board decisions, a leap over earlier ...

Researchers have built an explainable ensemble deep learning framework that fuses four transfer learning models using CMAES optimization to classify ...

A machine learning model called Amylo-Detect uses routine electronic health record data to identify patients at risk for cardiac amyloidosis, ...