Cancer has been characterized as a heterogeneous disease consisting of many different
subtypes. The early diagnosis and prognosis of a cancer type have become a necessity in …

Background Breast cancer is the most common cancer in women worldwide, with a great
diversity in outcomes among individual patients. The ability to accurately predict a breast …

In today's healthcare setting, the accurate and timely diagnosis of breast cancer is critical for
recovery and treatment in the early stages. In recent years, the Internet of Things (IoT) has …

This research studies a support vector machine (SVM)-based ensemble learning algorithm
for breast cancer diagnosis. Illness diagnosis plays a critical role in designating treatment …

Breast cancer (BC) is the most commonly found disease among women all over the world.
The early diagnosis of breast cancer can potentially reduce the mortality rate and increase …

Preeclampsia is one of the leading causes of maternal and fetal morbidity and mortality. Due
to the lack of effective preventive measures, its prediction is essential to its prompt …

In light of recent advances in biomedical computing, big data science, and precision
medicine, there is a mammoth demand for establishing algorithms in machine learning and …

Advancements are constantly being made in oncology, improving prevention and treatment
of cancers. To help reduce the impact and deadliness of cancers, they must be detected …

With the recent advancements in analyzing high-volume, complex, and unstructured data,
modern learning methods are playing an increasingly critical role in the field of personalized …

Cancer is a collection of diseases that involves growing abnormal cells with the potential to
invade or spread to the body. Breast cancer is the second leading cause of cancer death …