Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 21,371 to 21,380 of 216,627 articles

A machine learning approach coupling immediate and lagged drivers to predict sand and dust storms in Northern China.

Journal of environmental management May 10, 2026
Under global climate change, sand and dust storms (SDS) in Northern China have exhibited new spatiotemporal evolution characteristics. To investigate SDS driving mechanisms, this study integrated multi-source remote sensing and reanalysis data (2005-... read more 

Spatial management of riverine methane (CH4) emissions based on landscape drivers in the Yangtze River Basin.

Journal of environmental management May 10, 2026
Methane (CH4) is a significant greenhouse gas linked to key climate change drivers, garnering heightened global focus. However, existing CH4 risk management approaches lack spatial coordination for basin systems. Here, we combined hydrological simula... read more 

Trade-offs and synergies of ecosystem services in high density cities: Revealing nonlinear driving mechanisms through machine learning.

Journal of environmental management May 10, 2026
Metropolises are confronted with ecosystem degradation driven by rapid urbanization and continuously intensified human activities, posing significant challenges to human well-being and urban sustainable development. Identifying the trade-offs and syn... read more 

Near-infrared imaging-based high-content analysis for label-free assessment of internal cellular heterogeneity in spheroid.

Journal of bioscience and bioengineering May 10, 2026
Non-invasive analysis of spheroid quality was essential because spheroids better recapitulated in vivo-like cell-cell and cell-extracellular matrix (ECM) interactions than two-dimensional cultures. However, routine non-invasive methods to assess inte... read more 

Applications of artificial intelligence in nuclear medicine.

Zeitschrift fur medizinische Physik May 10, 2026
Artificial intelligence (AI) has vast potential to reshape nuclear medicine. Applications can be found at every step of the processing workflow, including image acquisition, image reconstruction, enhancement, and registration, segmentation, extractio... read more 

CHINTEXDB-PERU28: A unique dataset of traditional textile iconographies from Chinchero, Peru for cultural preservation and image recognition.

Data in brief May 10, 2026
This dataset was collected during on-site fieldwork conducted in the district of Chinchero, located in the province of Urubamba, Cusco, Peru, a region internationally recognized for its rich Andean textile tradition rooted in Inca Culture heritage. T... read more 

Interpretable machine learning with SHAP analysis identifies redox-modulating dietary antioxidants for predicting accelerated biological aging.

Experimental gerontology May 10, 2026
BACKGROUND: Aging is a complex biological process characterized by progressive functional decline across multiple physiological systems, and biological age provides a more accurate reflection of an individual's aging status than chronological age. Di... read more 

Machine learning and regional homogeneity reveal early and subtle brain changes in type 1 diabetes.

Journal of neuroradiology = Journal de neuroradiologie May 10, 2026
BACKGROUND AND PURPOSE: Type 1 diabetes mellitus (T1DM) usually begins early in life, and its development impacts brain functioning and cognitive processing. The present study examined alterations in spontaneous brain activity in young adults with T1... read more 

SedNet: A physics-informed operator-learning framework for rapid sedimentation velocity analytical ultracentrifugation analysis.

International journal of pharmaceutics May 10, 2026
To date, analyzing data from sedimentation velocity analytical ultracentrifugation (SV-AUC) experiments has exclusively been performed using finite element method or other numerical solver-based techniques. These methods are slow, requiring repeated ... read more 

Predicting length of stay in the pediatric intensive care unit at a tertiary center in Saudi Arabia using machine learning.

International journal of medical informatics May 10, 2026
BACKGROUND: Prolonged stay in pediatric intensive care units (PICUs) is associated with increased mortality risk, elevated healthcare costs, and diminished critical care capacity. Accurate early prediction of length of stay (LOS) may facilitate resou... read more 
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