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Diagnostic Decision-Making Variability Between Novice and Expert Optometrists for Glaucoma: Comparative Analysis to Inform AI System Design.
JMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
Response Theory via Generative Score Modeling.
Phys Rev Lett
December 2024
Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
We introduce an approach for analyzing the responses of dynamical systems to external perturbations that combines score-based generative modeling with the generalized fluctuation-dissipation theorem. The methodology enables accurate estimation of system responses, including those with non-Gaussian statistics. We numerically validate our approach using time-series data from three different stochastic partial differential equations of increasing complexity: an Ornstein-Uhlenbeck process with spatially correlated noise, a modified stochastic Allen-Cahn equation, and the 2D Navier-Stokes equations.
View Article and Find Full Text PDFMental Health Disparities by Sexual Orientation and Gender Identity in the All of Us Research Program.
JAMA Netw Open
January 2025
Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California.
Importance: Limited research explores mental health disparities between individuals in sexual and gender minority (SGM) populations and cisgender heterosexual (non-SGM) populations using national-level data.
Objective: To explore mental health disparities between SGM and non-SGM populations across sexual orientation, sex assigned at birth, and gender identity within the All of Us Research Program.
Design, Setting, And Participants: This cross-sectional study used survey data and linked electronic health records of eligible All of Us Research Program participants from May 31, 2017, to June 30, 2022.
Comparative Efficacy and Acceptability of Non-surgical Treatments with or without Exercise for Diastasis Recti Abdominis in Postpartum Women: A Network Meta-Analysis of Randomized Controlled Trials.
Sports Med
January 2025
Department of Nutrition, China Medical University, Taichung, Taiwan.
Background: Diastasis recti abdominis (DRA), commonly occurring in postpartum women, is not only an aesthetic issue but is also highly associated with functional impairments. Various conservative treatment modalities have been employed in clinical practice to alleviate DRA. However, the comparative efficacy of these non-surgical treatments for improving the inter-recti distance (IRD) remains to be determined.
View Article and Find Full Text PDFEnhanced O-glycosylation Site Prediction Using Explainable Machine Learning Technique with Spatial Local Environment.
Bioinformatics
January 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.
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