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Change surface regression for nonlinear subgroup identification with application to warfarin pharmacogenomics data.
Biometrics
January 2025
Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Singapore.
Pharmacogenomics stands as a pivotal driver toward personalized medicine, aiming to optimize drug efficacy while minimizing adverse effects by uncovering the impact of genetic variations on inter-individual outcome variability. Despite its promise, the intricate landscape of drug metabolism introduces complexity, where the correlation between drug response and genes can be shaped by numerous nongenetic factors, often exhibiting heterogeneity across diverse subpopulations. This challenge is particularly pronounced in datasets such as the International Warfarin Pharmacogenetic Consortium (IWPC), which encompasses diverse patient information from multiple nations.
View Article and Find Full Text PDFArtificial intelligence in clinical settings: a systematic review of its role in language translation and interpretation.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
Background: Addressing language barriers through accurate interpretation is crucial for providing quality care and establishing trust. While the ability of artificial intelligence (AI) to translate medical documentation has been studied, its role for patient-provider communication is less explored. This review evaluates AI's effectiveness in clinical translation by assessing accuracy, usability, satisfaction, and feedback on its use.
View Article and Find Full Text PDFEffects of Social Structure on Effective Population Size Change Estimates.
Evol Appl
January 2025
Instituto Gulbenkian de Ciência Oeiras Portugal.
Most methods currently used to infer the "demographic history of species" interpret this expression as a history of population size changes. The detection, quantification, and dating of demographic changes often rely on the assumption that population structure can be neglected. However, most vertebrates are typically organized in populations subdivided into social groups that are usually ignored in the interpretation of genetic data.
View Article and Find Full Text PDFChallenges and opportunities for validation of AI-based new approach methods.
ALTEX
January 2025
National Institutes of Health, National Institute for Environmental Health Sciences, DTT/NICEATM, Durham, NC, USA.
The integration of artificial intelligence (AI) into new approach methods (NAMs) for toxicology rep-resents a paradigm shift in chemical safety assessment. Harnessing AI appropriately has enormous potential to streamline validation efforts. This review explores the challenges, opportunities, and future directions for validating AI-based NAMs, highlighting their transformative potential while acknowledging the complexities involved in their implementation and acceptance.
View Article and Find Full Text PDFPenalized G-estimation for effect modifier selection in a structural nested mean model for repeated outcomes.
Biometrics
January 2025
Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 1G1, Canada.
Effect modification occurs when the impact of the treatment on an outcome varies based on the levels of other covariates known as effect modifiers. Modeling these effect differences is important for etiological goals and for purposes of optimizing treatment. Structural nested mean models (SNMMs) are useful causal models for estimating the potentially heterogeneous effect of a time-varying exposure on the mean of an outcome in the presence of time-varying confounding.
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