'While this is a promising area of development, AI-based evidence synthesis tools should not be
considered a ‘panacea’ or ‘cure all’ for the pressures imposed by an ever-expanding evidence base.
Given potential trade-offs, and a lack of information on unintended consequences, it is important that tools aren’t applied uncritically to resolve workload pressures'
“Our conversations with CILIP and attending the CILIP conference, is about helping make as many librarians as possible aware of the YouTube health initiative, and the credible health information available on the platform. And also that YouTube is a place you should feel comfortable directing your library visitors to for health information.” News release from CILIP - worth being aware of for patient information?
Key findings highlight Google Scholar, ResearchGate, Semantic Scholar, and Lens as leading options for FWC searching, with Lens providing superior download capabilities. For BWC searching, the Web of Science Core Collection can be recommended over Scopus for accuracy. BWC information from publisher databases such as IEEE Xplore or ScienceDirect was generally found to be the most accurate, yet only available for a limited number of articles
Editorial. Digital platforms and artificial intelligence's (AI) influence on our daily lives often go unnoticed. From the algorithms that support our smartphones and driverless vehicles to the medical diagnostic systems used by health professionals, AI is increasingly taking over decision-making tasks traditionally performed by humans. While enhancing human efficiency, this shift also introduces a myriad of ethical and legal uncertainties that demand our attention.
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his study aimed to examine health information seeking attitudes and behaviors in an academic-based employee wellness program before and after health literacy workshops were developed and facilitated by an academic health sciences librarian.
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Given the vast quantity of literature available, a key challenge of conducting rapid evidence syntheses is the time and effort required to manually screen large search results sets to identify and include all studies relevant to the research question within an accelerated timeline. To overcome this challenge, the NCCMT investigated the integration of artificial intelligence (AI) technologies into the title and abstract screening stage of the rapid review process to expedite the identification of studies relevant to the research question.
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This study aimed to establish quality criteria to assist patients, caregivers, and the public in evaluating the reliability of online health information.
While ChatGPT has gained popularity in various domains, it may not be the ideal focus for medical professionals due to its reliance on language pattern prediction rather than direct fact retrieval, potentially leading to inaccurate outputs. We emphasize the limitations of ChatGPT's training data, which mainly come from non-specialized sources and may result in misleading answers in highly specialized medical domains. We advocate for a shift towards specialized medical large language models (LLMs) that are trained using authoritative medical databases, supplemented by human validation, to ensure accuracy and completeness of data.
How to optimize the systematic review process using AI tools
Nicholas Fabiano, Arnav Gupta, Nishaant Bhambra, Brandon Luu, Stanley Wong, Muhammad Maaz, Jess G. Fiedorowicz … See all authors
First published: 23 April 2024
https://doi.org/10.1002/jcv2.12234
Nicholas Fabiano, Arnav Gupta and Nishaant Bhambra contributed equally to this paper.
We introduce Get Free Copy (https://getfreecopy.com), a web-based platform designed to streamline the search for biomedical literature across major repositories like arXiv, bioRxiv, medRxiv, and PubMed Central (PMC). Addressing challenges posed by paywalls and fragmented databases, it offers a unified interface for efficient retrieval of free, legitimate copies of biomedical literature. The platform's implementation involves a Node.js backend and dynamic front-end display, enhancing accessibility and research efficiency. As an open-source project, Get Free Copy represents a significant contribution to the open-access movement, inviting global researcher collaboration for further development.
J. Li, Y. Shen, L. Ho, W. Brandt, C. Grier, P. Hall, Y. Homayouni, A. Koekemoer, D. Schneider, и J. Trump. (2023)cite arxiv:2301.04177Comment: 23 pages, 10 figures (Fig 9 is the key figure). Submitted to ApJ. The full figure set and ancillary data products can be found at ftp://quasar.astro.illinois.edu/public/sdssrm/paper_data/Li_2023_HST_host.
S. Chang, Y. Yang, K. Seon, A. Zabludoff, и H. Lee. (2022)cite arxiv:2212.09630Comment: 42 pages, 27 figures, accepted for publication in ApJ, Comments welcome!.