The future of disease detection, treatment, and prevention may very well lie in data-driven
healthcare. Here, we take stock of where things stand and highlight certain emerging issues …

In healthcare, medical practitioners employ various imaging techniques such as CT, X-ray,
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …

Nowadays, breast cancer is the most prevalent and jeopardous disease in women after lung
cancer. During the past few decades, a substantial amount of cancer cases have been …

Breast cancer is mostly a female disease, but it may affect men as well even at a
considerably lower percentage. An automated diagnosis system should be built for early …

Intrusion detection is mainly achieved by using optimization algorithms. The need for
optimization algorithms for intrusion detection is necessitated by the increasing number of …

Cancer is a dreadful disease. Millions of people died every year because of this disease.
Neural networks are currently a burning research area in medical scienc It is very essential …

The experts' decisions and evaluating the patients' data are the most significant parts
affecting the breast cancer analysis. For early breast cancer detection, numerous techniques …

Recent advancements in the internet, social media, and internet of things (IoT) devices have
significantly increased the amount of data generated in a variety of formats. The data must …

Hepatitis C is an ailment that causes inflammation of the liver and leads to serious liver
damage. In previous research, the accuracy of the model wasn't that accurate but the …

Breast cancer is the second leading cause of mortality among female cancer patients
worldwide. Early detection of breast cancer is considerd as one of the most effective ways to …