AIMC Topic: Support Vector Machine

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Predictive Modeling of DNA Damage Outcomes: Classification of Mutational Determinants Using Augmented Machine Learning Techniques.

Chemical research in toxicology
The mutational outcome of DNA damage as a direct result of constant chemical assault is governed by major factors, including the structure and nature of damage, replication, and repair machinery . The role of the size of the adduct, adduct-flanking b...

Developing highly accurate machine learning models for optimizing water quality management decisions in tilapia aquaculture.

Scientific reports
The optimization of water quality management is crucial for the success and sustainability of tilapia aquaculture. This study presents a novel approach for developing a decision-support system by comparing various machine learning models to predict o...

Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study.

Scientific reports
Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric mag...

Development and validation of a model for predicting depression risk in primary palmar hyperhidrosis: a cross-sectional retrospective observational study.

BMJ open
OBJECTIVE: Primary palmar hyperhidrosis (PPH), characterised by excessive palm sweating, significantly impacts patients' physiology, psychology, self-esteem, work, life and social interactions. The incidence of depression is higher among PPH patients...

EEG workload estimation and classification: a systematic review.

Journal of neural engineering
Electroencephalography (EEG) has evolved into an indispensable instrument for estimating cognitive workload in various domains. Machine Learning (ML) and deep learning (DL) techniques have been increasingly employed to develop accurate workload estim...

Artificial intelligence in student management systems to enhance academic performance monitoring and intervention.

Scientific reports
In recent years, the integration of artificial intelligence (AI) in student management systems (SMS) has gained significant attention, particularly for monitoring academic performance and predicting at-risk students. Traditional approaches often lack...

A machine learning approach for detection of claustrophobic brain activity in electroencephalography.

Scientific reports
Claustrophobia, a phobia with a specific unreasonable and excessive fear of enclosed spaces, can have a considerable impact on an individual's life. Electroencephalography (EEG) has been a tool with potential for studying neural processes in anxiety ...

Optimizing high dimensional data classification with a hybrid AI driven feature selection framework and machine learning schema.

Scientific reports
Feature selection (FS) is critical for datasets with multiple variables and features, as it helps eliminate irrelevant elements, thereby improving classification accuracy. Numerous classification strategies are effective in selecting key features fro...

Machine learning-based forecasting of air quality index under long-term environmental patterns: A comparative approach with XGBoost, LightGBM, and SVM.

PloS one
Air pollution is a global problem that threatens environmental sustainability and severely affects public health. Monitoring air quality and predicting future pollution levels are critical for creating effective environmental policies and enabling in...

Prediction of changes in suitable habitats for tea plants in China's four major tea-producing regions based on machine learning models.

PloS one
Under the background of ongoing global climate warming, clarifying the spatiotemporal dynamics of suitable habitats for tea plants and their potential impact on forest ecosystems is essential for promoting sustainable tea industry development and eco...