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Support Vector Machine

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Multi-view learning with enhanced multi-weight vector projection support vector machine.

Neural networks : the official journal of the International Neural Network Society
Multi-view learning aims on learning from the data represented by multiple distinct feature sets. Various multi-view support vector machine methods have been successfully applied to classification tasks. However, the existed methods often face the pr...

Addressing Missing Data Challenges in Geriatric Health Monitoring: A Study of Statistical and Machine Learning Imputation Methods.

Sensors (Basel, Switzerland)
In geriatric healthcare, missing data pose significant challenges, especially in systems used for frailty monitoring in elderly individuals. This study explores advanced imputation techniques used to enhance data quality and maintain model performanc...

Machine learning based prediction models for the prognosis of COVID-19 patients with DKA.

Scientific reports
Patients with Diabetic ketoacidosis (DKA) have increased critical illness and mortality during coronavirus diseases 2019 (COVID-19). The aim of our study was to develop a predictive model for the occurrence of critical illness and mortality in COVID-...

A machine learning-based model for predicting the risk of cognitive frailty in elderly patients on maintenance hemodialysis.

Scientific reports
Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality of life. Early identification of at-risk individuals and timely intervention are essential. Neverthel...

A Deep Learning Approach for Mental Fatigue State Assessment.

Sensors (Basel, Switzerland)
This study investigates mental fatigue in sports activities by leveraging deep learning techniques, deviating from the conventional use of heart rate variability (HRV) feature analysis found in previous research. The study utilizes a hybrid deep neur...

Supervised learning approaches for predicting Ebola-Human Protein-Protein interactions.

Gene
The goal of this research work is to predict protein-protein interactions (PPIs) between the Ebola virus and the host who is at risk of infection. Since there are very limited databases available on the Ebola virus; we have prepared a comprehensive d...

Using Inertial Measurement Units and Machine Learning to Classify Body Positions of Adults in a Hospital Bed.

Sensors (Basel, Switzerland)
In hospitals, timely interventions can prevent avoidable clinical deterioration. Early recognition of deterioration is vital to stopping further decline. Measuring the way patients position themselves in bed and change their positions may signal when...

Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis.

Scientific reports
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlight...

Classification Prediction of Hydrocephalus After Intercerebral Haemorrhage Based on Machine Learning Approach.

Neuroinformatics
In order to construct a clinical classification prediction model for hydrocephalus after intercerebral haemorrhage(ICH) to guide clinical treatment decisions, this paper retrospectively analyses the clinical data of 844 cases of ICH and hydrocephalus...