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Chain of Risks Evaluation (CORE): A framework for safer large language models in public mental health.
Psychiatry Clin Neurosci
January 2025
Shanghai Artificial Intelligence Laboratory, Shanghai, China.
Large language models (LLMs) have gained significant attention for their capabilities in natural language understanding and generation. However, their widespread adoption potentially raises public mental health concerns, including issues related to inequity, stigma, dependence, medical risks, and security threats. This review aims to offer a perspective within the actor-network framework, exploring the technical architectures, linguistic dynamics, and psychological effects underlying human-LLMs interactions.
View Article and Find Full Text PDFEvaluating human ability to distinguish between ChatGPT-generated and original scientific abstracts.
Updates Surg
January 2025
Department of Surgery, St. Paul's Hospital, 1081 Burrard St., Vancouver, BC, V6Z 1Y6, Canada.
This study aims to analyze the accuracy of human reviewers in identifying scientific abstracts generated by ChatGPT compared to the original abstracts. Participants completed an online survey presenting two research abstracts: one generated by ChatGPT and one original abstract. They had to identify which abstract was generated by AI and provide feedback on their preference and perceptions of AI technology in academic writing.
View Article and Find Full Text PDFIdentification of Cell Fate Determining Transcription Factors for Generating Brain Endothelial Cells.
Stem Cell Rev Rep
January 2025
Stem Cell Institute, Department of Development and Regeneration, KU Leuven, O&N IV Herestraat 49, Leuven, 3000, Belgium.
Reliable models of the blood-brain barrier (BBB), wherein brain microvascular endothelial cells (BMECs) play a key role in maintenance of barrier function, are essential tools for developing therapeutics and disease modeling. Recent studies explored generating BMEC-like cells from human pluripotent stem cells (hPSCs) by mimicking brain-microenvironment signals or genetic reprogramming. However, due to the lack of comprehensive transcriptional studies, the exact cellular identity of most of these cells remains poorly defined.
View Article and Find Full Text PDFIdentification of a metabolic-immune signature associated with prognosis in colon cancer and exploration of potential predictive efficacy of immunotherapy response.
Clin Exp Med
January 2025
Department of General Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, Guangdong, China.
The role of metabolic reprogramming of the tumor immune microenvironment in cancer development and immune escape has increasingly attracted attention. However, the predictive value of differences in metabolism-immune microenvironment on the prognosis of colon cancer (CC) and the response to immunotherapy have not been elucidated. The aim of this study was to investigate changes in metabolism and immune profile of CC and to identify a reliable signature for predicting prognosis and therapeutic response.
View Article and Find Full Text PDFForensic sex classification by convolutional neural network approach by VGG16 model: accuracy, precision and sensitivity.
Int J Legal Med
January 2025
Centro de Estatística e Aplicações Universidade de Lisbao, CEAUL, Faculdade de Ciências da Universidade de Lisboa no Bloco C6 - Piso 4, Lisboa, 1749-016, Portugal.
Introduction: In the reconstructive phase of medico-legal human identification, the sex estimation is crucial in the reconstruction of the biological profile and can be applied both in identifying victims of mass disasters and in the autopsy room. Due to the inherent subjectivity associated with traditional methods, artificial intelligence, specifically, convolutional neural networks (CNN) may present a competitive option.
Objectives: This study evaluates the reliability of VGG16 model as an accurate forensic sex prediction algorithm and its performance using orthopantomography (OPGs).
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