Artificial Intelligence Medical Compendium

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

Showing 40,991 to 41,000 of 223,737 articles

Uncertainty Exploration of Deep Learning Enabled Fast Multidimensional NMR Spectroscopy of Proteins.

Analytical chemistry Mar 17, 2026
Deep learning (DL) has shown great promise in accelerating multidimensional NMR spectroscopy with high-accuracy reconstruction. Nevertheless, its practical deployment requires not only high accuracy but also reliability evaluations along with the pre... read more 

zERExtractor: An Automated Platform for Enzyme-Catalyzed Reaction Data Extraction from Scientific Literature.

Journal of chemical information and modeling Mar 17, 2026
The rapid expansion of enzyme reaction literature has created a major bottleneck in database curation, leaving vast amounts of enzyme-substrate-condition relationships unstructured and inaccessible for DL-driven modeling. How to fully utilize the enz... read more 

"Successful Aging" with Generative AI: Cultural and Ethical Challenges in Representing Aging through Synthetic Imagery.

The Gerontologist Mar 17, 2026
Synthetic imagery produced by Generative Artificial Intelligence (GenAI) is rapidly transforming how aging is visually represented and culturally understood. However, the accuracy and representational adequacy of these outputs require further examina... read more 

Deep survival modelling to predict future cognitive impairment in unimpaired adults.

The journals of gerontology. Series A, Biological sciences and medical sciences Mar 17, 2026
BACKGROUND: Predicting Alzheimer's disease (AD)-related cognitive impairment (CI) among cognitively normal (CN) adults enables meaningful disease modification through early intervention and enrichment of clinical trials. METHODS: A deep survival mode... read more 

CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning.

Nature communications Mar 17, 2026
Predicting crystal properties is essential for understanding structure-property relationships and accelerating material discovery. However, conventional approaches like experimental measurements or density functional theory calculations are resource-... read more 

Reliable uncertainty estimates in deep learning with efficient Metropolis-Hastings algorithms.

Nature communications Mar 17, 2026
Approaching problems with data-driven models often requires reliable uncertainty estimates. Bayesian neural networks can offer these for deep learning models. Without the knowledge to set informative prior distributions, sampling methods such as Hami... read more 

Structural evolution of carbon frameworks realizes in vitro interfacial transport in metabolically reprogrammed senescent cells for senolysis.

Nature communications Mar 17, 2026
Integrating the diagnostic and therapeutic functions of drugs poses challenges due to specific structural design requirements. However, the trial-and-error dilemma in performance-driven structural evolution of nanomaterials is unsatisfactory. Here, w... read more 

High-fidelity single-frame computational super-resolution using signal-preserving denoising-enabled deconvolution.

Nature communications Mar 17, 2026
Computational super-resolution (SR) methods enable nanoscale imaging from single-frame wide-field or spinning-disk confocal images without hardware modifications, yet face limitations: statistical restoration suffers from noise and artifacts, while d... read more 

A multi-focus oral panoramic x-ray image dataset based on pixel-level annotations.

Scientific data Mar 17, 2026
The dataset is a comprehensive, large-scale collection of panoramic X-ray images developed to advance research in dental artificial intelligence. It comprises 8,655 de-identified images and over 30,186 pixel-level annotations of lesion regions. These... read more 

Context-aware synthetic promoter design using neural networks enables rewiring of eukaryotic transcriptional networks.

NPJ systems biology and applications Mar 17, 2026
Gene regulation through promoter engineering is a cornerstone of synthetic biology, enabling precise control over transcriptional networks. However, experimental approaches remain labor-intensive. While artificial neural networks (ANNs) have improved... read more 
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