Artificial Intelligence Medical Compendium

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

Showing 18,621 to 18,630 of 214,544 articles

Machine learning-based analysis of the relationship between brain lesion sites and swallowing and cognitive functions in stroke patients.

Scientific reports May 14, 2026
Stroke-related dysphagia is influenced by brain damage location and cognitive impairment, but its mechanisms remain unclear. In this study, we aimed to clarify the mechanisms by which brain damage causes dysphagia and cognitive function in 246 patien... read more 

A two-stage OOD-aware approach for mosquito species detection based on RT-DETRv2.

Scientific reports May 14, 2026
Mosquitoes are important vectors of infectious diseases, and accurate species identification is essential for effective surveillance and control. Traditional image-based identification methods are labor-intensive, while existing deep learning models ... read more 

Integrating nano crystal sensor with explainable deep learning for nutrients and microplastic-toxicity detection.

Scientific reports May 14, 2026
This work proposes a simulation-based photonic-AI sensing framework for soil nutrient and microplastic detection. This framework integrates a 2D dual-ring cavity photonic crystal (PhC) sensor with a Deep & Cross Network model (DCN). The PhC sensor de... read more 

Comparative hyperparameter optimization of object detection models for precision monitoring of cucumber beetles and similar insects on yellow sticky cards.

Scientific reports May 14, 2026
Computer vision presents a great opportunity for improving pest monitoring in agriculture, particularly for yellow sticky traps, a critical component in IPM. However, despite the growing interest in applying object detection models for insect identif... read more 

On the usage of artificial intelligence for identifying main attributes and predicting neonatal sepsis.

Scientific reports May 14, 2026
During the neonatal period, newborns are more susceptible to developing conditions and diseases due to their fragility of the transition and adaptation to the extrauterine environment. Neonatal sepsis is one of the leading causes of morbidity and mor... read more 

Hybrid data-driven assessment and optimization strategies for municipal solid waste generation.

Scientific reports May 14, 2026
This study presents a comprehensive, harmonized dataset and an interpretable analytical framework for assessing per-capita waste generation (PCWG) across 36 Indian states and union territories. The research employs a robust data preprocessing methodo... read more 

Design and machine learning-based optimization of a graphene-driven funnel shaped THz MIMO antenna for 6G applications.

Scientific reports May 14, 2026
This research study investigates several techniques, such as simulation and an RLC equivalent circuit model, to evaluate antenna performance. The key novelty of this work lies in the integration of supervised machine learning-assisted optimization wi... read more 

Predicting dynamic individual out-of-hospital cardiac arrest risks using explainable machine learning: a multicenter study in China.

NPJ digital medicine May 14, 2026
Out-of-hospital cardiac arrest (OHCA) poses a significant public health challenge, with limited tools available for dynamic risk estimation under changing environmental conditions. This study aimed to develop and validate an OHCA risk prediction mode... read more 

Performance evaluation of fly-ash and silica-fume based geopolymer concrete at different alkaline molarities with machine learning-based strength prediction.

Scientific reports May 14, 2026
The high environmental impact of conventional Portland cement has driven the need for sustainable alternative binders with improved performance characteristics. Geopolymer concrete (GPC), particularly using industrial by-products such as fly ash and ... read more 

A human-in-the-loop explanation framework for morphologically transparent AI predictions from whole-slide images.

NPJ digital medicine May 14, 2026
Deep learning models enable the prediction of clinical endpoints from whole-slide images (WSIs), but many such models function as "black boxes", lacking transparency about whether and which histomorphological patterns drive their predictions, hinderi... read more 
Popular Topics
Recent Journals