AIMC Topic: Machine Learning

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The Application of Artificial Intelligence in Spine Surgery: A Scoping Review.

Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews
BACKGROUND: A comprehensive review on the application of artificial intelligence (AI) within spine surgery as a specialty remains lacking.

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.

Frontiers in immunology
BACKGROUND: The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related to BAM and FAM could offer a deeper u...

The Association of Elevated Depression Levels and Life's Essential 8 on Cardiovascular Health With Predicted Machine Learning Models and Interpretations: Evidence From NHANES 2007-2018.

Depression and anxiety
The association between depression severity and cardiovascular health (CVH) represented by Life's Essential 8 (LE8) was analyzed, with a novel focus on ranked levels and different ages. Machine learning (ML) algorithms were also selected aimed at pr...

Prediction of lumbar disc degeneration based on interpretable machine learning models: retrospective cohort study.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: The paraspinal muscles play a critical role in maintaining lumbar spine stability, and different muscles may have varying impacts on lumbar disc degeneration (LDD). However, studies exploring these relationships remain relatively ...

Aflatoxin detection in naturally contaminated peanuts based on vision transformer and multi-scale convolutional fusion.

Food chemistry
Aflatoxin is a highly toxic substance found in peanuts, posing a serious threat to human health. To address this issue, an improved 1D-MCFViT model combining the Vision Transformer with multi-scale convolutional fusion is proposed to detect aflatoxin...

TCH: A novel multi-view dimensionality reduction method based on triple contrastive heads.

Neural networks : the official journal of the International Neural Network Society
Multi-view dimensionality reduction (MvDR) is a potent approach for addressing the high-dimensional challenges in multi-view data. Recently, contrastive learning (CL) has gained considerable attention due to its superior performance. However, most CL...

A multi-domain constraint learning system inspired by adaptive cognitive graphs for emotion recognition.

Neural networks : the official journal of the International Neural Network Society
Neuroscience shows that the brain stimulated by external information can induce functional responses to emotions, which can be measured and analyzed by electroencephalogram (EEG). Most existing works focus on extracting specific spatial topological i...

Comprehensive analyses: Using machine learning models for mortality prediction in the intensive care unit of internal medicine.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research
Mortality prediction in the intensive care unit (ICU) is essential in patient management. Emerging methods such as machine learning (ML) can be employed to predict ICU patients' mortality. Patients receiving treatment in the ICU of the internal medic...

Machine Learning-Based Algorithm to Predict Procedural Success in a Large European Cohort of Hybrid Chronic Total Occlusion Percutaneous Coronary Interventions.

The American journal of cardiology
CTOs are frequently encountered in patients undergoing invasive coronary angiography. Even though technical progress in CTO-PCI and enhanced skills of dedicated operators have led to substantial procedural improvement, the success of the intervention...

A coupled machine-learning and sensitivity analysis framework to link dust activity in the Tigris-Euphrates basin to climatic and human-induced drivers.

Environmental research
This study analyzes the impact of climate-related stressors and water resources development in the Tigris-Euphrates basin on regional dust storm intensity and frequency. To this end, we first utilize remote sensing data on Aerosol Optical Depth (AOD)...