A broad range of medical diagnoses is based on analyzing disease images obtained
through high-tech digital devices. The application of artificial intelligence (AI) in the …

Support vector machine (SVM) is a widely used pattern classification method that its
classification accuracy is greatly influenced by both kernel parameter setting and feature …

We performed a systematic review of several pattern analysis approaches for classifying
breast lesions using dynamic, morphological, and textural features in dynamic contrast …

As a common screening and diagnostic tool, Fine Needle Aspiration Biopsy (FNAB) of the
suspicious breast lumps can be used to distinguish between malignant and benign breast …

In this paper, a new support vector machines (SVM) parameter tuning scheme that uses the
fruit fly optimization algorithm (FOA) is proposed. Termed as FOA-SVM, the scheme is …

Preoperative differentiation of complicated and uncomplicated appendicitis is challenging.
The research goal was to construct a new intelligent diagnostic rule that is accurate, fast …

Breast cancer death rates are higher than any other cancer in American women. Machine
learning-based predictive models promise earlier detection techniques for breast cancer …

Background The goal of this exploratory study was to develop and assess a prediction
model which can potentially be used as a biomarker of breast cancer, based on …

Breast cancer is one of the primary causes of death among the women worldwide, and the
accurate diagnosis is one of the most significant steps in breast cancer treatment. Data …

Support vector machine (SVM) is a well-regarded machine learning algorithm widely
applied to classification tasks and regression problems. SVM was founded based on the …