Artificial Intelligence Medical Compendium

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

Showing 56,761 to 56,770 of 227,153 articles

Learning from the successes and failures of early artificial intelligence (AI) adoption for drug discovery in Big BioPharma.

Expert opinion on drug discovery
INTRODUCTION: AI has tremendous potential to reduce time and costs taken to discover and develop new medical entities. As technology evolves, it is essential to learn from successes and failures to realign expectations for scientists, stakeholders an... read more 

Reviewing the Artificial Intelligence Boost for Accelerating the Development of Novel Antimicrobial Peptides.

Journal of applied microbiology
Antimicrobial resistance (AMR) is one of the most critical public health threats of the 21st century and is projected to become a leading cause of mortality by 2050. The World Health Organization (WHO) recognizes AMR as a top priority in its 2030 res... read more 

Application of AI-Driven Multi-Dimensional Food Printing Technology for Valorization of Food By-Products.

Journal of agricultural and food chemistry
Food by-products are rich in nutrients but are often discarded, causing resource waste and environmental burden. Traditional additive manufacturing (AM) struggles with these materials due to inconsistent rheology, unstable transformations, and comple... read more 

Discovery and cultivation of prokaryotic taxa in the age of metagenomics and artificial intelligence.

The ISME journal
Despite advances in sequencing, microbial genomics, and cultivation techniques, the vast majority of prokaryotic species remain uncultured, which is a persistent bottleneck in microbiology and microbial ecology. This perspective outlines a conceptual... read more 

RNA modifications in cancer and their detection: a review.

Japanese journal of clinical oncology
Ribonucleic acid (RNA) modifications, once viewed as static structural features, are now recognized as dynamic regulators of the 'epitranscriptome' that shape RNA fate. In cancer, dysregulation of RNA-modification writers, erasers, and readers reprog... read more 

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment.

Journal of computational biology : a journal of computational molecular cell biology
Mathematical modeling in systems toxicology enables a comprehensive understanding of the effects of pharmaceutical substances on cardiac health. However, the complexity of these models limits their widespread application in early drug discovery. In t... read more 

Gut microbiome signatures associated with depression and obesity.

mSystems
UNLABELLED: Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink to gut microbiome dysfunction. Here, we performed a case-control study with a total of 105 subjects... read more 

Mechanism Based Hierarchical Machine Learning for High-Throughput Quantitative Prediction of Estrogenic, Androgenic, and Thyroid Disruption Activities.

Environmental science & technology
Although qualitative predictions of endocrine-disrupting chemicals (EDCs) are well established, quantitative high-throughput models remain underdeveloped due to data heterogeneity and mechanistic complexity. To address this gap, we developed a mechan... read more 

Deciphering Key Descriptors for Scaling Relationships in Graphene-Supported Ptn Clusters via Machine Learning.

Small (Weinheim an der Bergstrasse, Germany)
Subnano clusters have emerged as a promising class of electrocatalysts, enabling efficient utilization of noble metals and superior activity for key electrochemical reactions. However, their fluxional nature and complex structure-activity relationshi... read more 

Distinct clinical clusters of paediatric patients with status epilepticus: Retrospective cohort study.

Developmental medicine and child neurology
AIM: To characterize the clinical features, management, and outcomes of paediatric patients with status epilepticus, and to explore whether distinct clinical subgroups can be identified from clinical descriptions. METHOD: This was an exploratory retr... read more