Artificial Intelligence Medical Compendium

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

Showing 581 to 590 of 200,021 articles

Rapid monitoring of drought and salinity stress responses in wheat via potential Raman-derived biomarkers and traditional biochemical indicators.

Scientific reports Jun 2, 2026
Abiotic stresses such as drought and salinity significantly constrain the productivity of in vitro-grown wheat (Triticum aestivum L.) by disrupting its biochemical and physiological homeostasis. Rapid, non-destructive, and data-driven diagnostic appr... read more 

The Open Materials 2024 (OMat24) inorganic materials dataset and models.

Nature computational science Jun 2, 2026
The discovery and simulation of inorganic materials is core to diverse applications from climate change to semiconductor manufacturing. Artificial intelligence has the potential to dramatically accelerate materials simulation, discovery and design. A... read more 

An explainable machine learning approach to predict fragility fractures and the identification of important features.

Scientific reports Jun 2, 2026
In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using the data from the Canadian Multicentre Osteoporosis Study (CaMos) with participants aged 50 years or ... read more 

Missing-data-aware machine learning prediction of in-hospital major adverse cardiovascular events after primary percutaneous coronary intervention for ST-segment elevation myocardial infarction.

Scientific reports Jun 2, 2026
Machine learning (ML) offers opportunities to improve prognostication after ST-segment elevation myocardial infarction (STEMI), but real-world registries frequently contain incomplete data, and inappropriate handling of missingness may degrade perfor... read more 

Early antifungal resistance prediction based on MALDI-TOF mass spectrometry and machine learning.

Scientific reports Jun 2, 2026
Antimicrobial resistance (AMR) is a significant global health threat. Recent studies have shown that combining MALDI-TOF mass spectrometry with machine learning algorithms can accelerate AMR determination. However, these efforts have predominantly fo... read more 

Hybrid spatial-field attention network for meteorological data downscaling.

Scientific reports Jun 2, 2026
Near-surface weather variables play an important role in production. However, the coarse spatial resolution meteorological data in existing meteorological products limit their applicability in modern high-precision engineering and decision-making sce... read more 

Machine-learned dimethyl sulphide (DMS) for the North Atlantic (2002-2024) to support movement studies.

Scientific reports Jun 2, 2026
Dimethyl sulphide (DMS) serves as a key olfactory cue for seabird navigation, yet existing DMS products operate at coarse spatiotemporal resolutions (≥ 25 km, monthly) mismatched to the scales of individual movement decisions. We ask (I) whether mach... read more 

A large-scale vision foundation model for musculoskeletal radiographs.

NPJ digital medicine Jun 2, 2026
Artificial intelligence (AI) has shown promise in detecting and characterizing musculoskeletal diseases from radiographs. However, most existing models remain task-specific, annotation-dependent, and limited in their adaptability across diseases and ... read more 

Human expertise or artificial intelligence? A prospective study on nail disorder diagnosis.

NPJ digital medicine Jun 2, 2026
Artificial intelligence (AI) shows promise in analyzing patterns of nail disease. This prospective, comparative study compared the diagnostic performance of dermatologists with that of large language models (LLMs). We evaluated the diagnostic accurac... read more 

Design of an AI-based security anomaly detection system for IoT terminals based on the ViT-transformer fusion model.

Scientific reports Jun 2, 2026
The deep penetration of IoT terminals in water systems, healthcare, transportation, and other fields has exacerbated security threats such as cyber-physical attacks and traffic anomalies. However, traditional anomaly detection methods have limitation... read more 
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