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Exploring the Credibility of Large Language Models for Mental Health Support: Protocol for a Scoping Review.

JMIR Res Protoc

January 2025

Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.

Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.

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Rationale: Tobacco smoking is a well-established risk factor for idiopathic pulmonary fibrosis (IPF), yet the influence of early-life tobacco exposure on future IPF risk remains poorly understood.

Objectives: To test the hypothesis that early-life tobacco exposure may elevate the risk of developing IPF, with this effect potentially modified by genetic susceptibility to IPF and mediated through accelerated biological aging.

Methods: Using data from over 430,000 participants in the UK Biobank, we performed a prospective cohort study to examine the associations of maternal smoking around birth and age of smoking initiation with IPF risk.

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Purpose: Neurotypical individuals show a robust "global precedence effect (GPE)" when processing hierarchically structured visual information. However, the auditory domain remains understudied. The current research serves to fill the knowledge gap on auditory global-local processing across the broader autism phenotype under the tonal language background.

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Mammography is one of the main methods available for breast cancer screening in Brazil. However, differences in timely access and performance of the exam can be highlighted based on social determinants of health, considered relevant due to their influence on the health situation of a population. Thus, the present study aimed to identify the social determinants of health associated with access to and performance of mammography in Brazilian women.

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Acute kidney injury (AKI) is a frequent clinical complication lacking early diagnostic tests and effective treatments. Novel biomarkers have shown promise for enabling earlier detection, risk stratification, and guiding management of AKI. We conducted a systematic review to synthesize evidence on the efficacy of novel biomarkers for AKI detection and management.

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