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The association between multilingual experience factors and cognitive functioning in older adults: A Lifelines study.
J Gerontol B Psychol Sci Soc Sci
January 2025
Linguistics and English as a Second Language, Faculty of Arts, University of Groningen, Groningen, the Netherlands.
Objectives: The complex life experience of speaking two or more languages has been suggested to preserve cognition in older adulthood. This study aimed to investigate this further by examining the relationship between multilingual experience variables and cognitive functioning in a large cohort of older adults in the diversely multilingual north of the Netherlands.
Method: 11,332 older individuals participating in the Lifelines Cohort Study completed a language experience questionnaire.
"The Brain is…": A Survey of the Brain's Many Definitions.
Neuroinformatics
January 2025
Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, 760 Westwood Plaza, Los Angeles, CA, 90024, USA.
A reader of the peer-reviewed neuroscience literature will often encounter expressions like the following: 'the brain is a dynamic system', 'the brain is a complex network', or 'the brain is a highly metabolic organ'. These expressions attempt to define the essential functions and properties of the mammalian or human brain in a simple phrase or sentence, sometimes using metaphors or analogies. We sought to survey the most common phrases of the form 'the brain is…' in the biomedical literature to provide insights into current conceptualizations of the brain.
View Article and Find Full Text PDFLeveraging Large Language Models to Enhance Dermatology Clinical Trial Patient Recruitment and Retention.
J Invest Dermatol
January 2025
Department of Dermatology, Stanford University, Stanford, California, USA; Department of Biomedical Data Science, Stanford University, Stanford, California, USA. Electronic address:
From promise to practice: challenges and pitfalls in the evaluation of large language models for data extraction in evidence synthesis.
BMJ Evid Based Med
December 2024
RTI International, Research Triangle Park, North Carolina, USA.
Integrating Model-Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation.
Clin Transl Sci
January 2025
Global Biometrics and Data Management, Pfizer Research and Development, New York, New York, USA.
The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate intricate processes involved in drug absorption, distribution, metabolism, and excretion, as well as pharmacokinetics and pharmacodynamics. Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug-target interactions from big data, enabling more accurate predictions and novel hypothesis generation.
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