Artificial Intelligence Medical Compendium

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

Showing 21,081 to 21,090 of 216,348 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 

A call for clarity: a unified checklist for reporting use of large language models in writing scientific manuscripts.

Research integrity and peer review May 10, 2026
The rapid integration of generative artificial intelligence (Gen AI) into academic writing has outpaced the establishment of consistent norms for responsible and transparent disclosure. Leading organizations including the International Committee of M... read more 

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

Discover oncology May 10, 2026
The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates targeted delivery, cytotoxic action, and non-invasive imaging into a unified clinical feedback loop. Th... read more 

Determinants and Machine Learning Prediction of Subtherapeutic Sodium Valproate Concentrations in Epilepsy Management in Xinjiang, China.

European journal of drug metabolism and pharmacokinetics May 10, 2026
BACKGROUND AND OBJECTIVE: Valproic acid is a classic antiepileptic drug; however, it is characterized by a narrow therapeutic window, limited safety margin, and marked individual variability. Therapeutic drug monitoring has become a key approach for ... read more 

Dynamic machine learning model integrating resting energy expenditure for predicting postoperative complications after gastrectomy for gastric cancer.

Journal of cancer research and clinical oncology May 10, 2026
PURPOSE: To investigate whether perioperative resting energy expenditure (REE) dynamics improve prediction of postoperative complications after gastrectomy for gastric cancer. METHODS: We retrospectively analyzed 193 patients who underwent elective g... read more 

STAID: A Self-Refining Deep Learning Framework for Spatial Cell-Type Deconvolution with Biologically Informed Modeling.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) May 10, 2026
Spatial transcriptomics provides high-throughput measurement of gene expression while retaining spatial context; however, inferring accurate cell-type compositions within individual spots remains a major challenge. Here, we present STAID, a unified f... read more 
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