Artificial Intelligence Medical Compendium

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

Showing 43,491 to 43,500 of 224,055 articles

Artificial intelligence-based prognostic models in acute myeloid leukemia: systematic review and meta-analysis.

Blood neoplasia Mar 10, 2026
Machine learning and deep learning tools have been proposed to improve survival prediction in acute myeloid leukemia (AML), but comparative benchmarks remain unclear. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 se... read more 

Bad Bunny: A Tale of Artificial Intelligence.

Nursing research Mar 10, 2026
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Predicting soymilk odors using a multilayer perceptron neural network model.

Food research international (Ottawa, Ont.) Mar 10, 2026
The presence of undesirable beany odors in soymilk products is a long-lasting issue for the soymilk manufacturers as it largely affects the consumers acceptance. Promising soybean varieties that generate satisfactory soymilk odors (SV-SSO) may offer ... read more 

Precise and high-throughput origin discrimination for green coffee beans by mass spectrometry-based metabolic analysis.

Food research international (Ottawa, Ont.) Mar 10, 2026
Fraud involving falsely labeled origins remains a significant risk in the trade of plant foods like green coffee beans, due to a lack of precise and high-throughput origin discrimination tools. Here, we for the first time employ a high-performance fe... read more 

The role of artificial intelligence in enhancing non-invasive quality monitoring in fresh food products supply chains: A comprehensive review.

Food research international (Ottawa, Ont.) Mar 10, 2026
Fresh food products are highly perishable and prone to quality deterioration throughout the supply chain, while conventional invasive monitoring methods suffer from low efficiency, destructiveness, and limited real-time capability. In recent years, n... read more 

Exploring relaxation features for rapid identification of olive oil adulteration via low-field nuclear magnetic resonance integrated with chemometrics.

Food research international (Ottawa, Ont.) Mar 10, 2026
Low-field nuclear magnetic resonance (LF-NMR) is a non-destructive analytical technique utilized for relaxation spectral fingerprinting, which shows great potential in detecting commercial food fraud. This study developed an analytic framework to ide... read more 

Experimentally paired high- and low-resolution confocal fluorescence microscopy dataset for deep-learning super-resolution imaging of tooth dentin porosity.

Data in brief Mar 10, 2026
The proposed dataset provides experimentally acquired high- and low-resolution confocal laser scanning microscopy images of dentin porosity, split into classified image patches that can be used for paired or unpaired super-resolution training. Porous... read more 

Advances in In silico predictive models for DDI prediction: Implications and practical applications in drug discovery.

Drug metabolism and pharmacokinetics Mar 10, 2026
Advances in machine learning and artificial intelligence have recently extended to the quantitative prediction of drug-drug interaction (DDI). Because DDIs arise from diverse mechanisms and the required level of predictive accuracy varies with both t... read more 

Principles and approaches applied for foodborne microbial risk assessment: a scoping review of concepts, limitations and future directions.

Food microbiology Mar 10, 2026
Microbiological risk assessment (MRA) is a cornerstone of food safety governance, enabling sound science to set food safety standards, guidelines, and recommendations, that aim to ensure consumer protection and facilitate international trade. This sc... read more 

A machine learning-based model to predict multi-time-point prognosis for acute-on-chronic hepatitis B liver failure.

iScience Mar 10, 2026
Our prognostic model and mobile application enable multi-time-point prognostic evaluation for patients with acute-on-chronic hepatitis B liver failure, thereby improving patient care and facilitating clinical decision-making for liver transplantation... read more 
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