AIMC Topic: Support Vector Machine

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Advances in artificial intelligence for diabetes prediction: insights from a systematic literature review.

Artificial intelligence in medicine
Diabetes mellitus (DM), a prevalent metabolic disorder, has significant global health implications. The advent of machine learning (ML) has revolutionized the ability to predict and manage diabetes early, offering new avenues to mitigate its impact. ...

Enhanced non-invasive machine learning approach for early colorectal cancer detection: Predictive modeling and validation in a Jordanian cohort.

Computers in biology and medicine
BACKGROUND: Colorectal cancer (CRC) ranks as the third most prevalent cancer worldwide, posing significant public health challenges. Late-stage detection often results in poor treatment outcomes, elevating mortality rates. The economic and psychologi...

Evaluation of blood- and urine-derived biomarkers for machine learning prediction models of osteoarthritis in elderly patients: A feasibility study.

Computer methods and programs in biomedicine
BACKGROUND: Osteoarthritis (OA) is a common degenerative joint disease, particularly affecting individuals aged >50 years. It deteriorates quality of life and restricts physical activity in the elderly. Early diagnosis of OA is crucial for effective ...

Machine learning-based detection and quantification of red blood cells in Cholistani cattle: A pilot study.

Research in veterinary science
This study presents the first account of using machine learning to detect and count normal and abnormal red blood cells (RBCs), including tear-drop cells and schistocytes, in Cholistani cattle from Pakistan. A Support Vector Machine (SVM) model was a...

Detection of COVID-19, lung opacity, and viral pneumonia via X-ray using machine learning and deep learning.

Computers in biology and medicine
The COVID-19 pandemic has significantly strained healthcare systems, highlighting the need for early diagnosis to isolate positive cases and prevent the spread. This study combines machine learning, deep learning, and transfer learning techniques to ...

The analysis of motion recognition model for badminton player movements using machine learning.

Scientific reports
This study aims to comprehensively analyze and classify the badminton players' swing actions by combining the theoretical frameworks of quantum mechanics and machine learning. A badminton stroke recognition method based on Quantum Convolutional Neura...

Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM.

Scientific reports
This study aims to enhance computers' ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. It proposes a metaphor recognition algorithm that combines a Convolut...

Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics.

Scientific reports
To investigate the prediction of a model constructed by combining machine learning (ML) with clinical features and ultrasound radiomics in the clinical staging of cervical cancer. General clinical and ultrasound data of 227 patients with cervical can...

Comparative Analysis of Feature Extraction Methods and Machine Learning Models for Predicting Osteoporosis Prevalence.

Journal of medical systems
This study systematically examined the impact of three feature selection techniques (Boruta, Extreme gradient boosting (XGBoost), and Lasso) for optimizing four machine learning models (Random forest (RF), XGBoost, Logistic regression (LR), and Suppo...

Hyperspectral imaging combined with DBO-SVM for the germination prediction of thermally damaged seeds.

Analytical methods : advancing methods and applications
Healthy development of the maize seed industry plays a key role in the effective supply of agricultural products and ensures national food security. Thermal damage to seeds significantly affects crop yield, seed vitality and nutritional value, making...