Performance of support vector machines in pneumonia detection using chest x-ray images from Filipino cohorts
Studies have shown that computer-aided diagnosis (CAD) systems significantly improve the accuracy and speed of radiologic interpretations of chest x-ray images (CXR). In this study, we developed a machine learning-based CXR image classifier by optimizing support vector machine (SVM) to distinguish pneumonia from normal CXR images…
Artificial intelligence for liver disease detection using ultrasound images
Artificial intelligence (AI) could facilitate an automated and accurate early detection of liver diseases. In this study, we optimized via transfer learning Visual Geometry Group 19 (VGG19), a convolutional neural network (CNN) architecture to classify liver ultrasound images into different disease classes…
Machine learning-based automation of COVID-19 screening using clinical dataset
Fast and effective screening of COVID-19 patients can help decrease its mortality rate. In this study, we employed machine learning methods on clinical datasets for automated COVID-19 screening…
Identification of candidate genomic regions by integrating cluster analysis and genome-wide association studies
By identifying genomic variants responsible for life-threatening complex disorders, genome-wide association studies (GWAS) has gained great potential in improving precision medicine…
Machine learning approach to the classification of hepatitis B surface antigen seroclearance in hepatitis B virus
This study used an integrated machine learning (ML) classification technique to classify patients with or without seroclearance of hepatitis B surface antigen (HBsAg) using single nucleotide polymorphism (SNP).…