Results 161 to 170 of about 14,226,764 (313)
Références bibliographiques du dossier « Ce que l’école enseigne à tous »
Hélène Beaucher
doaj +1 more source
Artificial intelligence in anesthesia: comparison of the utility of ChatGPT v/s google gemini large language models in pre-anesthetic education: content, readability and sentiment analysis. [PDF]
Sharma P +7 more
europepmc +1 more source
Fall enrollment in higher education.
Mode of access: Internet.Continues: National Center for Education Statistics.
National Center for Education Statistics.
core
National Assessment of Vocational Education
The National Assessment of Vocational Education (NAVE) is a congressionally-mandated evaluation of the 1998 Carl D. Perkins Vocational and Technical Education Act and of the implementation and outcomes of vocational education in the United States.
National Assessment of Vocational Education
core
High‐risk bladder cancer is typically treated with Bacillus Calmette‐Guérin (BCG), but 30–40% of patients relapse. No FDA‐ or CE‐approved biomarkers currently predict or prognosticate BCG failure. We systematically reviewed the literature and identified 72 eligible studies, revealing several promising biomarkers associated with BCG treatment response ...
Rui Ribeiro‐Pereira +7 more
wiley +1 more source
Comparison of Diabetes Education Content Experienced by Blind and Nonblind People With Diabetes. [PDF]
Heydarian N +6 more
europepmc +1 more source
In head and neck squamous cell carcinoma (HNSCC) p53 and p63 exert opposite roles on the transcription regulation of the lncRNA NEAT1. Under basal conditions, p53 levels are low and p63 represses NEAT1 expression. Upon genotoxic stress, p53 is rapidly induced, displacing p63 from the NEAT1 promoter leading to NEAT1 transcriptional activation and ...
Sara De Domenico +5 more
wiley +1 more source
AI-Generated Graduate Medical Education Content for Total Joint Arthroplasty: Comment. [PDF]
Daungsupawong H, Wiwanitkit V.
europepmc +1 more source
RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source

