Artificial Intelligence Medical Compendium

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

Showing 1,061 to 1,070 of 200,219 articles

Ideological and political education behavior recognition by artificial intelligence transformers.

Scientific reports Jun 1, 2026
This study aims to enhance the objectivity and scalability of process evaluation in ideological and political education (IPE) classrooms, while addressing the high cost, strong subjectivity, and limited capacity of traditional manual classroom observ... read more 

Attention-enhanced GNN model for fungal disease classification in spinach leaves using monospectral imaging.

Scientific reports Jun 1, 2026
Plant leaf diseases must be detected and treated early to improve crop yield and reduce agricultural losses. However, pixel-level representations and the inability to be read limit the applicability of existing deep learning approaches to the agricul... read more 

A hybrid knowledge-based and evolutionary framework for fault diagnosis and optimization in power systems.

Scientific reports Jun 1, 2026
This paper presents a hybrid artificial intelligence framework designed to improve the diagnosis of error and subsequent optimization of operational efficiency in complex energy systems. By integrating knowledge-based systems with evolutionary algori... read more 

Self-supervised representation learning reveals explainable physiological structure in high-dimensional magnetocardiography.

NPJ digital medicine Jun 1, 2026
Artificial intelligence (AI) has shown strong performance in cardiology, but most approaches rely on sensing modalities whose physical limitations constrain available information. Magnetocardiography (MCG) records the cardiac magnetic field with less... read more 

Prediction of syncope recurrence after percutaneous closure of patent foramen ovale based on machine learning.

Scientific reports Jun 1, 2026
Patent foramen ovale (PFO) has been increasingly associated with otherwise unexplained syncope, but predictors of syncope recurrence after percutaneous closure remain unclear. This study aimed to develop and internally evaluate machine-learning model... read more 

Implementing Artificial Intelligence-Enabled Ambient Documentation Technology for Ambulatory Clinicians: An Innovation Evaluation.

Journal of general internal medicine Jun 1, 2026
BACKGROUND: Artificial intelligence (AI)-enabled "ambient" documentation may reduce clinician administrative burdens and improve care delivery, but implementation in clinical practice is complex. AIM: To evaluate the implementation of commercially av... read more 

Machine learning models for predicting postpartum convulsions using clinical indicators from PMA Ethiopia data.

Scientific reports Jun 1, 2026
Postpartum convulsions, defined as seizure episodes occurring after childbirth during the postpartum period, remain a major cause of maternal morbidity and mortality in Ethiopia. This study aimed to develop and validate machine learning models to pre... read more 

AI for predicting exacerbations in KIDs with asthma (AIRE-KIDS).

NPJ digital medicine Jun 1, 2026
Recurrent acute care visits are a common yet preventable outcome for many children with asthma. Machine learning (ML) applied to electronic medical records (EMR) may help identify children at high risk and enable targeted referral to preventative car... read more 

Improving seismic fault detection through fault-balanced patch extraction and deep learning networks (UNet, Efficient-UNet, and VGG19-UNet).

Scientific reports Jun 1, 2026
Accurate seismic fault detection is essential for reliable structural interpretation, reservoir characterization, and drilling risk mitigation. Conventional attribute-based methods often suffer from noise sensitivity, fragmented fault continuity, and... read more 

A deep learning approach for keratoconus detection using spatio-temporal features from corneal imaging.

Scientific reports Jun 1, 2026
Keratoconus is a progressive corneal disease that requires early and accurate detection to prevent severe visual impairment. This study presents a deep learning-based classification model for distinguishing between healthy and keratoconic eyes using ... read more 
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