AIMC Topic: Support Vector Machine

Clear Filters Showing 941 to 950 of 4975 articles

A Kernelized Classification Approach for Cancer Recognition Using Markovian Analysis of DNA Structure Patterns as Feature Mining.

Cell biochemistry and biophysics
Nucleotide-based molecules called DNA and RNA are essential for several biological processes that affect both normal and cancerous cells. They contain the critical genetic material needed for normal cell growth and functioning. The DNA structure patt...

Machine learning prediction of malaria vaccine efficacy based on antibody profiles.

PLoS computational biology
Immunization through repeated direct venous inoculation of Plasmodium falciparum (Pf) sporozoites (PfSPZ) under chloroquine chemoprophylaxis, using the PfSPZ Chemoprophylaxis Vaccine (PfSPZ-CVac), induces high-level protection against controlled huma...

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

Sensors (Basel, Switzerland)
The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditiona...

TSVM: Transfer Support Vector Machine for Predicting MPRA Validated Regulatory Variants.

IEEE/ACM transactions on computational biology and bioinformatics
Genome-wide association studies have shown that common genetic variants associated with complex diseases are mostly located in non-coding regions, which may not be causal. In addition, the limited number of validated non-coding functional variants ma...

Use of machine learning approaches to predict transition of retention in care among people living with HIV in South Carolina: a real-world data study.

AIDS care
Maintaining retention in care (RIC) for people living with HIV (PLWH) helps achieve viral suppression and reduce onward transmission. This study aims to identify the best machine learning model that predicts the RIC transition over time. Extracting f...

Comparison of Machine Learning Algorithms Fed with Mobility-Related and Baropodometric Measurements to Identify Temporomandibular Disorders.

Sensors (Basel, Switzerland)
Temporomandibular disorders (TMDs) refer to a group of conditions that affect the temporomandibular joint, causing pain and dysfunction in the jaw joint and related muscles. The diagnosis of TMDs typically involves clinical assessment through operato...

Identifying miRNA as biomarker for breast cancer subtyping using association rule.

Computers in biology and medicine
- This paper presents a comprehensive study focused on breast cancer subtyping, utilizing a multifaceted approach that integrates feature selection, machine learning classifiers, and miRNA regulatory networks. The feature selection process begins wit...

Identification of ion channel-related genes as diagnostic markers and potential therapeutic targets for osteoarthritis through bioinformatics and machine learning-based approaches.

Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
BACKGROUND: Osteoarthritis (OA) is a debilitating joint disorder characterized by the progressive degeneration of articular cartilage. Although the role of ion channels in OA pathogenesis is increasingly recognized, diagnostic markers and targeted th...

Combined interaction of fungicides binary mixtures: experimental study and machine learning-driven QSAR modeling.

Scientific reports
Fungicide mixtures are an effective strategy in delaying the development of fungicide resistance. In this research, a fixed ratio ray design method was used to generate fifty binary mixtures of five fungicides with diverse modes of action. The intera...

Discrimination of internal crack for rice seeds using near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
It is an important thing to identify internal crack in seeds from normal seeds for evaluating the quality of rice seeds (Oryza sativa L.). In this study, non-destructive discrimination of internal crack in rice seeds using near infrared spectroscopy ...