Results 221 to 230 of about 1,449,758 (311)
This study evaluated the educational impact of artificial intelligence (AI)‐navigation surgery that provides real‐time anatomical landmark recognition during laparoscopic cholecystectomy for medical students. Thirty students were randomized into surgeon‐guided, self‐learning, and AI‐learning groups, and their performance was assessed using Dice ...
Shigeo Ninomiya +8 more
wiley +1 more source
Using a nationwide Japanese inpatient database, we evaluated whether broad‐spectrum antibiotic prophylaxis improves postoperative outcomes after pancreatoduodenectomy compared with narrow‐spectrum antibiotics. In propensity score–weighted analyses of 45 099 patients, broad‐spectrum prophylaxis was associated with significantly lower rates of intra ...
Hiroki Kitagawa +10 more
wiley +1 more source
Engaging the Next Generation: Designing an Experiential Intensive Care Unit Workshop on Neurologic Emergencies for Medical Students From Diverse Backgrounds. [PDF]
Guinat M +6 more
europepmc +1 more source
Abstract This work experimentally validates the RESPONSE (Resilient Process cONtrol SystEm) framework as a solution for maintaining safe, continuous operation of cyber‐physical process systems under cyberattacks. RESPONSE implements a dual‐loop architecture that runs a networked online controller in parallel with a hard‐isolated offline controller ...
Luyang Liu +5 more
wiley +1 more source
AI in chemical engineering: From promise to practice
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew +4 more
wiley +1 more source
Implementation and utilization of Physical Examination Teaching Associate (PETA) programs: a scoping review. [PDF]
Hopkins H, Lewis K, Smith CM, Yelen ME.
europepmc +1 more source
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Criteria of teacher and students's didactic performances in psychology: the Peruvian university students' perceptions. [PDF]
Bazán-Ramírez A +8 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source

