Artificial Intelligence Medical Compendium

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

Showing 46,481 to 46,490 of 224,055 articles

Integrating Clinical Modeling and Machine Learning for Risk Assessment of Paracetamol and Other Nonsteroidal Anti-Inflammatory Drug Hypersensitivity in Children.

The journal of allergy and clinical immunology. In practice Feb 26, 2026
BACKGROUND: Nonsteroidal anti-inflammatory drug (NSAID) hypersensitivity is a common cause of drug-related reactions in children. Pre-test risk stratification may improve the safety and efficiency of drug provocation testing (DPT). OBJECTIVE: To deve... read more 

Deep learning assisted cell electrical signal analysis in impedance cytometry.

Analytical biochemistry Feb 26, 2026
In this study, we developed BioFluxNet, a 1D CNN-based algorithm for automated analysis of raw electrical signals in impedance cytometry to directly classify cell types and quantify cell counts. The network comprises three functional blocks: a featur... read more 

msCNN-PLM-FAD: Enhanced predicting FAD binding sites by using protein language representation combined with multiple separable windows convolutional neural networks.

Analytical biochemistry Feb 26, 2026
The FAD binding sites classification problem is crucial because it is directly related to many diseases, such as flavoprotein-associated diseases, developmental disorders, digestive and lipid metabolism abnormalities, anemia, cancer, cardiovascular d... read more 

From quantum feature maps to quantum reservoir computing: an applicative perspective.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Feb 26, 2026
We explore the interplay between two emerging paradigms: reservoir computing (RC) and quantum computing (QC). We observe how quantum systems featuring beyond-classical correlations and vast computational spaces can serve as non-trivial, experimentall... read more 

A methodology for accurate benchmarking of neural network accelerators using a high-level synthesis-based hardware generator.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Feb 26, 2026
As neural network models continue to grow in scale and complexity, specialized hardware accelerators have emerged to meet the increased demand for compute and memory. These accelerators employ a wide range of architectural innovations, making it chal... read more 

Towards efficient and reliable artificial intelligence through neuromorphic principles.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Feb 26, 2026
Artificial intelligence (AI) research today is largely driven by ever-larger neural network models trained on graphics processing units (GPUs). This paradigm has yielded remarkable progress, but it also risks entrenching a hardware lottery in which a... read more 

Resource constrained learning over wireless networks.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences Feb 26, 2026
It is anticipated that the next generation of wireless networks will incorporate artificial intelligence (AI) to a significant degree at all network layers. A major part of this trend is the migration of AI and machine learning functions to the netwo... read more 

A graph neural network-based method to identify lncRNA subcellular localizations.

Computational biology and chemistry Feb 26, 2026
The subcellular localizations of long non-coding RNAs (lncRNAs) are closely related to their biological functions and disease mechanisms. Existing methods for their identification have limitations in handling data imbalance and complex sequence struc... read more 

AATE-UNet automated assessment of inflammatory response in zebrafish larvae exposed to environmental risks.

Ecotoxicology and environmental safety Feb 26, 2026
In the evaluation of drugs/cosmetics toxicology/efficacy on livings, rapid assessment of inflammatory responses in zebrafish models is critical but hindered by labor-intensive manual neutrophil counting. To be addressed, this study developed the inno... read more 

Predicting aerobic granular sludge structural instability: An intelligent early-warning framework integrating convolutional neural network and fluorescence fingerprint features.

Journal of environmental management Feb 26, 2026
Aerobic granular sludge (AGS) was recognized as an innovative alternative superior to activated sludge processes, yet its development has been constrained by structural instability and the lack of early-warning methods for critical states. To address... read more 
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