AIMC Topic: Machine Learning

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Machine Learning-Based Clustering Using a 12-Lead Electrocardiogram in Patients With a Implantable Cardioverter Defibrillator to Identify Future Ventricular Arrhythmia.

Circulation journal : official journal of the Japanese Circulation Society Oct 1, 2024
BACKGROUND: Implantable cardioverter defibrillators (ICDs) reduce mortality associated with ventricular arrhythmia in high-risk patients with cardiovascular disease. Machine learning (ML) approaches are promising tools in arrhythmia research; however...
Arrhythmias, Cardiac Tachycardia, Ventricular Defibrillators, Implantable Retrospective Studies Female Aged Electrocardiography Cluster Analysis Male Middle Aged Humans Machine Learning
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Learning on manifolds without manifold learning.

Neural networks : the official journal of the International Neural Network Society Oct 1, 2024
Function approximation based on data drawn randomly from an unknown distribution is an important problem in machine learning. The manifold hypothesis assumes that the data is sampled from an unknown submanifold of a high dimensional Euclidean space. ...
Algorithms Humans Neural Networks, Computer Machine Learning
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Development of the machine learning model that is highly validated and easily applicable to predict radiographic knee osteoarthritis progression.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society Oct 1, 2024
Many models using the aid of artificial intelligence have been recently proposed to predict the progression of knee osteoarthritis. However, previous models have not been properly validated with an external data set or have reported poor predictive p...
Humans Machine Learning Retrospective Studies Middle Aged Disease Progression Female Radiography Aged Osteoarthritis, Knee Male
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Employing Machine Learning Models to Predict Potential α-Glucosidase Inhibitory Plant Secondary Metabolites Targeting Type-2 Diabetes and Their Validation.

Journal of chemical information and modeling Oct 1, 2024
The need for new antidiabetic drugs is evident, considering the ongoing global burden of type-2 diabetes mellitus despite notable progress in drug discovery from laboratory research to clinical application. This study aimed to build machine learning ...
Hypoglycemic Agents Plants alpha-Glucosidases Humans Glycoside Hydrolase Inhibitors Machine Learning Secondary Metabolism Diabetes Mellitus, Type 2
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Protocol for UAV fault diagnosis using signal processing and machine learning.

STAR protocols Oct 1, 2024
Unmanned aerial vehicles (UAVs) require fault diagnosis for safe operation. Here, we present a protocol for UAV fault diagnosis using signal processing and artificial intelligence. We describe steps for collecting vibration-based signal data, preproc...
Neural Networks, Computer Machine Learning Algorithms Signal Processing, Computer-Assisted Unmanned Aerial Devices
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Using machine learning modeling to identify childhood abuse victims on the basis of personality inventory responses.

Journal of psychiatric research Oct 1, 2024
Trauma is very common and associated with significant co-morbidity world-wide, particularly PTSD and frequently other mental health disorders. However, it can be challenging to identify victims of abuse as self-reports can be difficult to elicit due ...
Humans Machine Learning Female Child Abuse Personality Inventory Male Adolescent Child
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Development of learning-based predictive models for radiation-induced atrial fibrillation in non-small cell lung cancer patients by integrating patient-specific clinical, dosimetry, and diagnostic information.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Oct 1, 2024
BACKGROUND AND PURPOSE: Radiotherapy (RT) in non-small cell lung cancer (NSCLC) can induce cardiac adverse events, including atrial fibrillation (AF), despite advanced RT. This study integrates patient-specific information to develop learning-based m...
Carcinoma, Non-Small-Cell Lung Atrial Fibrillation Radiotherapy Dosage Chemoradiotherapy Radiation Injuries Middle Aged Deep Learning Lung Neoplasms Female Aged Male Humans Machine Learning
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Multi-instance learning for identifying high-risk subregions associated with synchronous distant metastasis in clear cell renal cell carcinoma.

Medical physics Oct 1, 2024
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common histological subtypes of renal tumors.
Image Processing, Computer-Assisted Support Vector Machine Neoplasm Metastasis Carcinoma, Renal Cell Kidney Neoplasms Risk Adult Male Middle Aged Tomography, X-Ray Computed Female Aged Humans Machine Learning
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Machine learning and radiomics for ventricular tachyarrhythmia prediction in hypertrophic cardiomyopathy: insights from an MRI-based analysis.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024
BACKGROUND: Myocardial fibrosis is often detected in patients with hypertrophic cardiomyopathy (HCM), which causes left ventricular (LV) dysfunction and tachyarrhythmias.
Adult Radiomics Male Machine Learning Retrospective Studies Female Predictive Value of Tests Cardiomyopathy, Hypertrophic Tachycardia, Ventricular Magnetic Resonance Imaging, Cine Middle Aged Contrast Media Magnetic Resonance Imaging Humans
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Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.

Acta radiologica (Stockholm, Sweden : 1987) Oct 1, 2024
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...
Aged, 80 and over Spinal Neoplasms Adult Spinal Fractures Radiomics Humans Tomography, X-Ray Computed Machine Learning Male Female Fractures, Compression Retrospective Studies Middle Aged Aged Diagnosis, Differential
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