We performed a meta-analysis of chemo-brain diagnostic, pooling sensitivities, and
specificities in order to assess the accuracy of a machine-learning (ML) algorithm in breast …

Featured Application The proposed solution provides a quick approach for the annotation of
the necessary training data to create an application-specific machine learning model that …

Medical anomaly identification using machine learning is a significant subject that has
received a lot of attention. Artificial neural networks' successor, deep learning, is a well …

Chronic kidney disease (CKD) is one of the causes of mortality in almost all countries across
the globe and the notable thing is its asymptomatic nature in the early stages. This disease …

This paper presents a novel approach for brain tumor detection using Steady-State Genetic
Algorithms for filter optimization and feature selection. The proposed method utilizes two …

Health is always the first thing to be taken care of particularly when a human being is taken
into consideration. Most of the people are unaware of hidden diseases inside their bodies …

This study aimed to compare three segmentation techniques—U-Net, Random Forest, and
Fuzzy C-Means—for malignant tumour detection in medical images. We used a publicly …

Medical imaging is a key tool used in healthcare to diagnose and prognose patients by
aiding the detection of a variety of diseases and conditions. In practice, medical image …

Image segmentation is a basic issue in machine vision. One of the important tasks of
machine vision and image processing is to recognize the pattern and one of the most …