Artificial Intelligence Medical Compendium

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

Showing 53,701 to 53,710 of 225,930 articles

A fast fully automated approach for evaluating calcified lesions in intravascular ultrasound.

European heart journal. Digital health
AIMS: Catheter-based coronary intervention is an effective treatment for acute coronary syndrome. However, calcified plaques pose significant challenges within these procedures, as they complicate stent deployment and passage of devices. This study p... read more 

A graph-based safe reinforcement learning method for multi-agent cooperation.

Neural networks : the official journal of the International Neural Network Society
Safety and Restricted Communication are two critical challenges faced by practical Multi-Agent Systems (MAS). However, most Multi-Agent Reinforcement Learning (MARL) algorithms that rely solely on reward shaping are ineffective in ensuring safety, an... read more 

Nitrilotriacetic acid functionalized gold nanopillars enable stochastic detection and deep learning analysis of prolines and hydroxyprolines by surface enhanced Raman spectroscopy.

Nanoscale
Proline hydroxylation is crucial for monitoring diseases related to collagen metabolism, analyzing metabolic pathways, and evaluating therapeutic or nutritional outcomes. However, the small differences in the hydroxyl group between prolines (Pro) and... read more 

Prediction of the low-temperature properties of electrolyte solvents for lithium-ion batteries via machine learning.

Nanoscale
Electrolytes with low melting points (MPs), high boiling points (BPs), and high dielectric constants (ε) can effectively mitigate performance degradation in lithium-ion batteries (LIBs) under low-temperature conditions. However, the lack of systemati... read more 

Disentangle-and-aggregate feature learning (DAFNet) for motor bearing fault diagnosis.

Scientific reports
To address the issues of parameter redundancy and low computational efficiency in traditional convolutional neural networks (CNNs) for motor bearing fault diagnosis, which are caused by increasing network depth, this paper proposes a Disentangle-and-... read more 

Comparative analysis of supervised and ensemble models with unsupervised exploration for alzheimer's disease prediction.

Scientific reports
Alzheimer's disease is a progressive neurodegenerative disorder characterized by memory loss and cognitive decline, with no known cure. Early detection of dementia, a primary manifestation of Alzheimer's disease, is critical to enable timely interven... read more 

Development and validation of a machine learning model based on interpretable clinical characteristics for preoperative prediction of Ki-67 expression in pituitary adenomas.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
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