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Transforming RN-Baccalaureate Education Using Insights From a National Faculty Needs Assessment.

Nurse Educ

January 2025

Author Affiliations: Arizona State University Edson College of Nursing and Health Innovation, Phoenix, Arizona (Dr Heywood); Wichita State University School of Nursing, Wichita, Kansas (Dr Williams); Southern New Hampshire University Nursing and Health Professions Department, Manchester, New Hampshire (Dr Blackwell); Bemidji State University Department of Nursing, Bemidji, Minnesota (Dr Hommes); University of Mississippi Medical Center School of Nursing, Jackson, Mississippi (Professor Franklin); and Boise State University School of Nursing, Boise, Idaho (Dr Nichols).

Background: The recent American Association of Colleges of Nursing (AACN) Essentials revision emphasizes direct clinical experiences across 4 spheres of care in RN-Baccalaureate (RN-B) education, creating challenges for online, asynchronous programs. Differentiating between prelicensure and postlicensure education complicates the integration of these requirements. Understanding RN-B faculty needs is critical for curricular transformation.

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Context: To address the severe fuel crisis and environmental pollution, the use of lightweight metal materials, such as AZ alloy, represents an optimal solution. This study investigates the mechanical behavior and deformation mechanism of AZ alloys under uniaxial compressive using molecular dynamics (MD) simulations. The influence of various compositions, grain sizes (GSs), and temperatures on the compressive stress, the ultimate compressive strength (UCS), compressive yield stress (CYS), Young's modulus (E), shear strain, phase transformation, dislocation distribution, and total deformation length is thoroughly examined.

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Background: Concept maps are a suitable method for teaching clinical reasoning (CR). For example, in a concept map, findings, tests, differential diagnoses, and treatment options can be documented and connected to each other. When combined with virtual patients, automated feedback can be provided to the students' concept maps.

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Ejtm3 experiences after ChatGPT and other AI approaches: values, risks, countermeasures.

Eur J Transl Myol

January 2025

A&C M-C Foundation for Translational Myology, Padua, Italy; Institute of Biomedical and Neural Engineering, Reykjavik University, Reykjavik, Iceland; Department of Digital Transformation, Landspitali University Hospital, Reykjavík.

We invariably hear that Artificial Intelligence (AI), a rapidly evolving technology, does not just creatively assemble known knowledge. We are told that AI learns, processes and creates, starting from fixed points to arrive at innovative solutions. In the case of scientific work, AI can generate data without ever having entered a laboratory, (i.

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Purpose: The goal of the study described in this protocol is to build a multimodal artificial intelligence (AI) model to predict abdominal aortic aneurysm (AAA) shrinkage 1 year after endovascular aneurysm repair (EVAR).

Methods: In this retrospective observational multicenter study, approximately 1000 patients will be enrolled from hospital records of 5 experienced vascular centers. Patients will be included if they underwent elective EVAR for infrarenal AAA with initial assisted technical success and had imaging available of the same modality preoperatively and at 1-year follow-up (CTA-CTA or US-US).

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