AIMC Topic: Support Vector Machine
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A machine learning-based model for predicting the risk of cognitive frailty in elderly patients on maintenance hemodialysis.
Scientific reports
Jan 20, 2025
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...
Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.
International journal of chronic obstructive pulmonary disease
Jan 20, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Speech Acoustics
Speech Production Measurement
Voice Quality
Male
Female
Predictive Value of Tests
Severity of Illness Index
Humans
Middle Aged
Reproducibility of Results
Functional Status
Speech
Prospective Studies
Disease Progression
Aged
Time Factors
Respiratory Function Tests
Prognosis
Lung
Pulmonary Disease, Chronic Obstructive
Support Vector Machine
A Deep Learning Approach for Mental Fatigue State Assessment.
Sensors (Basel, Switzerland)
Jan 19, 2025
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
Jan 17, 2025
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)
Jan 16, 2025
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
Jan 14, 2025
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
Jan 14, 2025
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...
Nonlinear feature selection for support vector quantile regression.
Neural networks : the official journal of the International Neural Network Society
Jan 13, 2025
This paper discusses the nuanced domain of nonlinear feature selection in heterogeneous systems. To address this challenge, we present a sparsity-driven methodology, namely nonlinear feature selection for support vector quantile regression (NFS-SVQR)...
Integrated of Hyperspectral Imaging and Machine Learning Algorithms for Nondestructive Detection of Therapeutic Properties of Plants.
Chemistry & biodiversity
Jan 13, 2025
The approaches used to determine the medicinal properties of the plants are often destructive, labor-intensive, time-consuming, and expensive, making it impossible to analyze their quality analysis online. Performance of hyperspectral imaging (HSI) i...
LMSST-GCN: Longitudinal MRI sub-structural texture guided graph convolution network for improved progression prediction of knee osteoarthritis.
Computer methods and programs in biomedicine
Jan 13, 2025
BACKGROUND AND OBJECTIVES: Accurate prediction of progression in knee osteoarthritis (KOA) is significant for early personalized intervention. Previous methods commonly focused on quantifying features from a specific sub-structure imaged at baseline ...
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