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Support Vector Machine

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Enhancing gait recognition by multimodal fusion of mobilenetv1 and xception features via PCA for OaA-SVM classification.

Scientific reports
Gait recognition has become an increasingly promising area of research in the search for noninvasive and effective methods of person identification. Its potential applications in security systems and medical diagnosis make it an exciting field with w...

Machine learning for accurate detection of small airway dysfunction-related respiratory changes: an observational study.

Respiratory research
BACKGROUND: The use of machine learning(ML) methods would improve the diagnosis of small airway dysfunction(SAD) in subjects with chronic respiratory symptoms and preserved pulmonary function(PPF). This paper evaluated the performance of several ML a...

Interpretable machine learning for dermatological disease detection: Bridging the gap between accuracy and explainability.

Computers in biology and medicine
Research on disease detection by leveraging machine learning techniques has been under significant focus. The use of machine learning techniques is important to detect critical diseases promptly and provide the appropriate treatment. Disease detectio...

Groundwater salinity modeling and mapping using machine learning approaches: a case study in Sidi Okba region, Algeria.

Environmental science and pollution research international
The groundwater salinization process complexity and the lack of data on its controlling factors are the main challenges for accurate predictions and mapping of aquifer salinity. For this purpose, effective machine learning (ML) methodologies are empl...

A stacking ensemble model for predicting the occurrence of carotid atherosclerosis.

Frontiers in endocrinology
BACKGROUND: Carotid atherosclerosis (CAS) is a significant risk factor for cardio-cerebrovascular events. The objective of this study is to employ stacking ensemble machine learning techniques to enhance the prediction of CAS occurrence, incorporatin...

Computational Insights into Reproductive Toxicity: Clustering, Mechanism Analysis, and Predictive Models.

International journal of molecular sciences
Reproductive toxicity poses significant risks to fertility and progeny health, making its identification in pharmaceutical compounds crucial. In this study, we conducted a comprehensive in silico investigation of reproductive toxic molecules, identif...

Machine learning analysis of lab tests to predict bariatric readmissions.

Scientific reports
The purpose of this study was to develop a machine learning model for predicting 30-day readmission after bariatric surgery based on laboratory tests. Data were collected from patients who underwent bariatric surgery between 2018 and 2023. Laboratory...

Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

Respiration; international review of thoracic diseases
INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning model based on endobronchial ultrasound (EBUS) to assist in diagnosing benign and malignant mediastinal and hilar lymph nodes (LNs).

Plasma-based near-infrared spectroscopy for early diagnosis of lung cancer.

Journal of pharmaceutical and biomedical analysis
Lung cancer (LC) continues to be a leading death cause in China, primarily due to late diagnosis. This study aimed to evaluate the effectiveness of using plasma-based near-infrared spectroscopy (NIRS) for LC early diagnosis. A total of 171 plasma sam...

PMTPred: machine-learning-based prediction of protein methyltransferases using the composition of k-spaced amino acid pairs.

Molecular diversity
Protein methyltransferases (PMTs) are a group of enzymes that help catalyze the transfer of a methyl group to its substrates. These enzymes play an important role in epigenetic regulation and can methylate various substrates with DNA, RNA, protein, a...