Artificial Intelligence Medical Compendium

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

Showing 43,371 to 43,380 of 224,055 articles

Bowtie-patterned MIM SERS platform assisted by machine learning for detection of pesticide residues in food matrices.

Talanta
The increasing use of pesticides and their mixtures poses a serious risk to human health and the environment. This increases the demand for simple, cost-effective, and reliable methods for detecting these residues. In this study, a highly sensitive i... read more 

TLR3 as a PANoptosis-related gene: a potential diagnostic biomarker and therapeutic target for diabetic retinopathy.

3 Biotech
UNLABELLED: WGCNA was used to identify DR-related PANoptosis genes, and the LASSO, SVM-RFE, and Random Forest machine learning models were then employed to identify key PANoptosis-related genes. The lncRNA-miRNA-TLR3 networks were constructed, and th... read more 

IDH enzyme inhibition in cancer therapy: mechanisms, mutational insights, and effects of IDH inhibitors in glioma, acute myeloid leukemia and chondrosarcoma.

3 Biotech
Isocitrate dehydrogenase (IDH) enzymes have recently emerged as a highly promising target for therapeutic intervention in cancer treatment. Mutations in IDH genes result in the production of the oncometabolite, D-2-hydroxyglutarate (D-2HG), which con... read more 

Explicable intensity-aware 3D cerebrovascular segmentation with planar representation.

Medical image analysis
Cerebrovascular segmentation provides valuable cues for cerebrovascular diseases. Deep learning has achieved remarkable success in cerebrovascular segmentation, but relies on colossal computing power. To address existing challenges, we studied the in... read more 

Memory like the human brain: A framework for decoding multimodal learning of brain-visual-linguistic features.

Medical image analysis
Decoding human visual neural representations is scientifically important for advancing research on brain-like intelligence. Existing research typically aligns neural signals captured by fMRI or EEG with visual and linguistic features, thereby enablin... read more 

Disparate size and stock status between two Sardina pilchardus stocks in northwest African waters.

Marine environmental research
Small pelagic species like the European sardine (Sardina pilchardus) are highly sensitive to fishing pressure and environmental variability. This study evaluates the impact of oceanographic changes on sardine growth and stock status in western Africa... read more 

AI-driven identification of a selective dual function inhibitor blocking HK2 activity and HK2-VDAC1 interaction displaying enhanced anticancer efficacy under hypoxia.

European journal of medicinal chemistry
Selective inhibition of hexokinase 2 (HK2) represents a promising therapeutic strategy due to the pivotal role of HK2 in the Warburg effect, enhancement of glycolysis and anti-apoptosis via HK2-Voltage-Dependent Anion Channel 1 (VDAC1) protein-protei... read more 

Impact of corrosive groundwater on water infrastructure and public health in the contiguous United States.

Water research
In U.S. drinking water systems, corrosion in aging iron (Fe) and lead (Pb) pipes imposes significant economic challenges, damages infrastructure, and presents public health risks. Despite these issues, large-scale detection of pipe corrosion remains ... read more 

Signal or noise? Evaluating commonly used attribution methods for explaining deep neural networks in electrocardiogram classification.

European heart journal. Digital health
AIMS: Attribution-based explainability methods are widely used in electrocardiogram (ECG) analysis to interpret predictions from 'black-box' deep neural networks (DNNs). To be useful in clinical applications, attribution methods must produce explanat... read more 

Structure from rank: Rank-order coding as a bridge from sequence to structure.

Neural networks : the official journal of the International Neural Network Society
Understanding how structured sequence information can be represented and generalized in neural systems is key to modeling the transition from acoustic input to emergent structure. In this study, we propose a rank-order based neural network inspired b... read more