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Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

Ann Intern Med

January 2025

Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).

Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.

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Alternative models of funding curiosity-driven research.

Proc Natl Acad Sci U S A

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Department of Psychology, University of Liverpool, Liverpool L69 7ZA, United Kingdom.

Funding of curiosity-driven science is the lifeblood of scientific and technological innovation. Various models of funding allocation became institutionalized in the 20th century, shaping the present landscape of research funding. There are numerous reasons for scientists to be dissatisfied with current funding schemes, including the imbalance between funding for curiosity-driven and mission-directed research, regional and country disparities, path-dependency of who gets funded, gender and race disparities, low inter-reviewer reliability, and the trade-off between the effort and time spent on writing or reviewing proposals and doing research.

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For most researchers, academic publishing serves two goals that are often misaligned-knowledge dissemination and establishing scientific credentials. While both goals can encourage research with significant depth and scope, the latter can also pressure scholars to maximize publication metrics. Commercial publishing companies have capitalized on the centrality of publishing to the scientific enterprises of knowledge dissemination and academic recognition to extract large profits from academia by leveraging unpaid services from reviewers, creating financial barriers to research dissemination, and imposing substantial fees for open access.

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Introduction: Metabolic dysfunction-associated steatotic liver disease (MASLD) has been linked to pancreatic diseases, but evidence from population-based studies with liver histology is lacking.

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