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Support Vector Machine

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Systematic review and epistemic meta-analysis to advance binomial AI-radiomics integration for predicting high-grade glioma progression and enhancing patient management.

Scientific reports 40341184
High-grade gliomas, particularly glioblastoma (MeSH:Glioblastoma), are among the most aggressive and lethal central nervous system tumors, necessitating advanced diagnostic and prognostic strategies. This systematic review and epistemic meta-analysis...
Artificial Intelligence Brain Neoplasms Disease Progression Glioma Humans Machine Learning Magnetic Resonance Imaging Prognosis Radiomics Support Vector Machine
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Enhancing mechanical ventilator reliability through machine learning based predictive maintenance.

Technology and health care : official journal of the European Society for Engineering and Medicine 40331554
BackgroundWith the advancement of Artificial Intelligence (AI), clinical engineering has witnessed transformative opportunities, enabling predictive maintenance of medical devices, optimization of healthcare workflows, and personalized patient care. ...
Algorithms Bayes Theorem Decision Trees Equipment Failure Humans Machine Learning Reproducibility of Results Respiration, Artificial Support Vector Machine Ventilators, Mechanical
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Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.

Scientific reports 40341247
An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global fu...
Activities of Daily Living Aged Aged, 80 and over Female Humans Inpatients Machine Learning Male Middle Aged Prognosis Prospective Studies Recovery of Function Stroke Stroke Rehabilitation Support Vector Machine Treatment Outcome
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Machine learning-based survival models for predicting rehospitalization of older hip fracture patients: a retrospective cohort study.

BMC musculoskeletal disorders 40340665
PURPOSE: To evaluate machine learning-based survival model roles in predicting rehospitalization after hip fractures to improve reduce the burden on the healthcare system.
Aged Aged, 80 and over Female Hip Fractures Humans Kaplan-Meier Estimate Machine Learning Male Patient Readmission Retrospective Studies Risk Assessment Support Vector Machine
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Impact of canny edge detection preprocessing on performance of machine learning models for Parkinson's disease classification.

Scientific reports 40355628
This study investigates the classification of individuals as healthy or at risk of Parkinson's disease using machine learning (ML) models, focusing on the impact of dataset size and preprocessing techniques on model performance. Four datasets are cre...
Bayes Theorem Decision Trees Humans Logistic Models Machine Learning Parkinson Disease Support Vector Machine
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Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction.

Frontiers in public health 40352838
INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools...
Forecasting Humans Incidence Lung Neoplasms Machine Learning Public Health Support Vector Machine United States
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Exploring Ovarian Cancer Prediction Models and Potential Markers Using Machine Learning.

Annals of clinical and laboratory science 40340886
OBJECTIVE: To develop machine learning models, facilitate a more accurate diagnosis of ovarian cancer (OC), and explore potential markers.
Adult Aged Area Under Curve Biomarkers, Tumor CA-125 Antigen Female Humans Machine Learning Middle Aged Neural Networks, Computer Ovarian Neoplasms ROC Curve Support Vector Machine
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Rapid identification of coffee species and origin using affordable multi-channel spectral sensor combined with machine learning.

Food research international (Ottawa, Ont.) 40356157
The rapid identification of coffee species and origin is critical for ensuring quality control and authenticity in the coffee industry. This study explores the use of an affordable multi-channel spectral sensor, AS7265X (410-940 nm), combined with ma...
Coffea Coffee Discriminant Analysis Indonesia Machine Learning Neural Networks, Computer Principal Component Analysis Quality Control Seeds Spectrum Analysis Support Vector Machine
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Dynamic bone recognition for robotic vertebral plate cutting via unit energy consumption and SVM optimized by PSO.

Scientific reports 40350530
Current orthopedic robots lack the ability to dynamically sense or accurately recognize bone layers during vertebral plate decompression surgery, limiting their ability to adjust actions in real time as skilled surgeons do. This study aims to improve...
Animals Bone Plates Principal Component Analysis Robotic Surgical Procedures Spine Support Vector Machine Swine
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Enhanced classification of tinnitus patients using EEG microstates and deep learning techniques.

Scientific reports 40335585
This study aims to deepen the understanding and classification of tinnitus through a comprehensive analysis of EEG signals utilizing innovative microstate analysis techniques and cutting-edge machine learning approaches. EEG data were collected from ...
Adult Deep Learning Electroencephalography Female Humans Male Middle Aged Support Vector Machine Tinnitus
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