Unveiling Early Detection And Prevention Of Cancer: Machine Learning And Deep Learning Approaches:

Abstract

This research discusses the use of machine learning and deep learning techniques for cancer detection and screening. The use of machine learning and deep learning algorithms enables survey specialists, including healthcare professionals, to increase the accuracy of risk assessments for diseases such as cancer, and hence identify the best time and techniques for screening. The use of these technologies enhances the accuracy of diagnosis while simultaneously aiding in the formulation of treatment regimens based on patients’ profiles. The Conventional approaches in cancer prevention and early detection sometimes act poorly as they sometimes do not cover many aspects of changes and variations of risks in people. Skin cancer is a prevailing issue, and the worldwide effects have amplified the importance of early and appropriate diagnosing. In previous years, the field of medical research has expanded through the use of machine learning and deep learning approaches, particularly in the diagnosis and classification of skin cancers. The importance of using machine learning and deep learning techniques in the early detection and prevention of cancer. The study emphasizes the importance of machine learning and deep learning approaches in the future struggle against cancer, which will necessitate the incorporation of early detection into normal operations. Due to the machine learning approach, multifaceted connections and relationships are found in high-dimensional data and hence sharper and individualized prophylactic measures. However, issues like quality of gathered data, interpretability of models, and of course, ethical issues are still there to hold back the progress of these technologies. In this regard, the present review seeks to provide detailed information regarding the current landscape of skin cancer research by showcasing the power of ML and DL models to the scholars, clinicians, and other healthcare professionals. This paper underscores the need for care and detection of cancer at an early stage as well as preventing the cancer illness. In particular, highlighting achievements along with unexplored opportunities for further development for this kind of research, this venture aims to introduce new advances in the field of skin cancer identification.