Artificial Intelligence Medical Compendium

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

Showing 47,421 to 47,430 of 224,199 articles

Machine learning prediction of metabolic-associated fatty liver disease in type 2 diabetes: Emphasizing data imputation and feature selection.

PloS one Feb 24, 2026
Metabolic-Associated Fatty Liver Disease (MAFLD) is common among Type 2 Diabetes (T2DM) patients. The coexistence of these conditions increases the risk of MAFLD progression and diabetes complications. Detecting MAFLD early is challenging due to its ... read more 

A fuzzy ZE-number group decision-making framework using BWM and MABAC for risk assessment in medicinal plant extraction.

PloS one Feb 24, 2026
The extraction of bioactive compounds from medicinal plants is a crucial process in pharmaceutical and herbal medicine industries, yet it presents numerous challenges that can compromise quality, efficiency, and standardization. This study integrates... read more 

You Only Look Once (YOLO) based machine learning algorithm for real-time detection of loop-mediated isothermal amplification (LAMP) diagnostics.

PloS one Feb 24, 2026
Loop-mediated isothermal amplification (LAMP) is a widely used rapid and affordable molecular DNA amplification method with minimal resource requirements. However, visual interpretation of results is subjective and prone to errors, leading to potenti... read more 

A deep learning framework for gait-based frailty classification using inertial measurement units.

PloS one Feb 24, 2026
Frailty in older adults leads to heightened vulnerability to adverse health outcomes, significantly burdening individuals and society by increasing healthcare costs and dependency. To address this issue, an advanced frailty assessment method combinin... read more 

Automatic segmentation of coronary plaques in coronary CT angiography using neural networks.

PloS one Feb 24, 2026
Rapid and accurate detection of coronary plaques on CCTA is critical for timely CAD diagnosis but is limited by reader workload and interobserver variability. Our objective was to evaluate the effectiveness of machine learning (ML) based on automated... read more 

Edge computing task scheduling mechanism based on multi-dimensional feature extraction and attention fusion.

PloS one Feb 24, 2026
In the edge computing environment, when existing task scheduling algorithms allocate resources for tasks, the central host of edge computing consumes more energy and processes fewer tasks successfully. To solve this problem, this paper proposes an ed... read more 

Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects.

ACS nano Feb 24, 2026
The optical properties of defects in solids produce rich physics, from gemstone coloration to single-photon emission for quantum networks. Essential to describing optical transitions is electron-phonon coupling, which can be predicted from first-prin... read more 

Cariology in pediatric dentistry: An updated evidence-based narrative review.

Community dental health Feb 24, 2026
Despite notable progress in understanding the pediatric dental caries area, its multifactorial etiology-including biofilm dynamics, dietary habits, host factors, and social determinants-the burden of untreated caries persists, particularly in socioec... read more 

Machine Learning Models for Mortality Prediction in Intensive Care Unit Patients With Ischemic Stroke Associated With Intracranial Artery Stenosis: Retrospective Cohort Study.

JMIR cardio Feb 24, 2026
BACKGROUND: Mortality prediction in intensive care unit (ICU) patients with ischemic stroke complicated by intracranial artery stenosis or occlusion remains difficult. Conventional scoring systems often lack discriminatory power and fail to provide i... read more 

Artificial Intelligence and Public Health Data in Emergencies: A Critical Issue in the Middle East.

The American journal of tropical medicine and hygiene Feb 24, 2026
Timely access to reliable public health data is a critical determinant of effective response to health emergencies, including disease outbreaks, climate-related health shocks, and humanitarian crises. Although artificial intelligence (AI) has been pr... read more 
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