Skin diseases frequently cause mental and physical distress and are major global health concern. Because early detection is crucial to successful treatment, accurate diagnosis is challenge for dermatologists as well. Diagnostic accuracy could be sign...
Diabetic Retinopathy, Cataract, and Glaucoma are major retinal diseases that require early detection to prevent irreversible vision loss. This study proposes a deep learning-based framework for the automated classification of retinal images into four...
BACKGROUND: The biological sciences are producing increasingly larger datasets for biomarker discovery. While common data models have been developed for medical terms as they relate to patient health outcomes, a data model that supports longitudinal ...
Metabolites play a crucial role in sustaining biological activities and are also a significant source of new drug development. Nuclear magnetic resonance (NMR) spectroscopy is one of the most important tools for identifying the structures of the meta...
Non-ST-elevation myocardial infarction (NSTEMI) in elderly diabetic patients presents unique challenges in risk assessment and prognosis prediction. This study aimed to develop and validate a machine learning-based mortality risk prediction model for...
Proceedings of the National Academy of Sciences of the United States of America
Dec 9, 2025
Here, we present an analysis of the growth and use of the Global Biodiversity Information Facility (GBIF) over the last 5 y. GBIF is the world's largest data integrator for biodiversity information and plays a central role in research across the biod...
Prognostic stratification of Hodgkin lymphoma (HL) patients in ICU remains challenging, with conventional scoring systems often overlooking pathophysiological biomarkers. This retrospective cohort study analyzed 1,908 HL patients from the MIMIC-IV da...
Chemistry (Weinheim an der Bergstrasse, Germany)
Dec 5, 2025
The identification of drug targets remains one of the most critical challenges in pharmaceutical research. The rapid progress of artificial intelligence (AI) is significantly advancing this landscape by enabling more efficient and accurate drug-targe...
BACKGROUND: Reusing long-term data from electronic health records is essential for training reliable and effective health artificial intelligence (AI). However, intrinsic changes in health data distributions over time-known as dataset shifts, which i...
OBJECTIVES: To develop a machine learning (ML)-based predictive model to determine the key predictors of dissatisfaction after occupational injury (OI).
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