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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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Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.

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PD-L1/PD-1 checkpoint inhibitors (CPIs) are mainstream agents for cancer immunotherapy, but the prognosis is unsatisfactory in solid tumor patients lacking preexisting T-cell reactivity. Adjunct therapy strategies including the intratumoral administration of immunostimulants aim to address this limitation. CpG oligodeoxynucleotides (ODNs), TLR9 agonists that can potentiate adaptive immunity, have been widely investigated to tackle PD-L1/PD-1 resistance, but clinical success has been hindered by inconsistent efficacy and immune-related toxicities caused by systemic exposure.

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Interventions to reduce non-prescription antimicrobial sales in community pharmacies.

Cochrane Database Syst Rev

January 2025

Global Health Nursing, Graduate School of Nursing Science, St. Luke's International University, Chuo-ku, Japan.

Background: Antimicrobial resistance (AMR) is a major global health concern. One of the most important causes of AMR is the excessive and inappropriate use of antimicrobial drugs in healthcare and community settings. Most countries have policies that require antimicrobial drugs to be obtained from a pharmacy by prescription.

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Aims: We aimed to explore atrial fibrillation (AF)-induced productivity losses in working-age atrial fibrillation patients and to estimate atrial fibrillation-related indirect costs.

Methods: Between 2014 and 2017, the Swiss Atrial Fibrillation prospective cohort study (Swiss-AF) enrolled 217 working-age patients with documented atrial fibrillation. Self-reported changes in professional activity and the reasons thereof were descriptively analysed over 8 years of follow-up or until patients reached the retirement age.

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