AIMC Topic: Support Vector Machine

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Classification of Three Anesthesia Stages Based on Near-Infrared Spectroscopy Signals.

IEEE journal of biomedical and health informatics
Proper monitoring of anesthesia stages can guarantee the safe performance of clinical surgeries. In this study, different anesthesia stages were classified using near-infrared spectroscopy (NIRS) signals with machine learning. The cerebral hemodynami...

Machine-learning-based prediction by stacking ensemble strategy for surgical outcomes in patients with degenerative cervical myelopathy.

Journal of orthopaedic surgery and research
BACKGROUND: Machine learning (ML) is extensively employed for forecasting the outcome of various illnesses. The objective of the study was to develop ML based classifiers using a stacking ensemble strategy to predict the Japanese Orthopedic Associati...

Mathematical modeling and numerical simulation of supercritical processing of drug nanoparticles optimization for green processing: AI analysis.

PloS one
In recent decades, unfavorable solubility of novel therapeutic agents is considered as an important challenge in pharmaceutical industry. Supercritical carbon dioxide (SCCO2) is known as a green, cost-effective, high-performance, and promising solven...

A machine learning-based prediction of hospital mortality in mechanically ventilated ICU patients.

PloS one
BACKGROUND: Mechanical ventilation (MV) is vital for critically ill ICU patients but carries significant mortality risks. This study aims to develop a predictive model to estimate hospital mortality among MV patients, utilizing comprehensive health d...

Auxiliary diagnostic method of Parkinson's disease based on eye movement analysis in a virtual reality environment.

Neuroscience letters
Eye movement dysfunction is one of the non-motor symptoms of Parkinson's disease (PD). An accurate analysis method for eye movement is an effective way to gain a deeper understanding of the nervous system function of PD patients. However, currently, ...

Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection.

TheScientificWorldJournal
Utilities face serious obstacles from power theft, which calls for creative ways to maintain income and improve operational effectiveness. This study presents a novel hybrid genetic artificial hummingbird algorithm-support vector machine classifier t...

Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Food chemistry
Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the prediction and generation patterns of HAAs is of great significance. In this study, genetic algorithm (GA) and support vector regression (SVR) are us...

Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta.

International journal of molecular sciences
Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matri...

PSSM-Sumo: deep learning based intelligent model for prediction of sumoylation sites using discriminative features.

BMC bioinformatics
Post-translational modifications (PTMs) are fundamental to essential biological processes, exerting significant influence over gene expression, protein localization, stability, and genome replication. Sumoylation, a PTM involving the covalent additio...

Predictors of Medical and Dental Clinic Closure by Machine Learning Methods: Cross-Sectional Study Using Empirical Data.

Journal of medical Internet research
BACKGROUND: Small clinics are important in providing health care in local communities. Accurately predicting their closure would help manage health care resource allocation. There have been few studies on the prediction of clinic closure using machin...