Survey on Cancer Diagnosis from Different Tests and Detection Methods with Machine and Deep Learning
Ghost Manoj Kumar, P. Sathish Kumar, V. Rajendran · Apple Academic Press eBooks · 2022
Cancer is one of the most dreaded and antagonistic diseases in the world, being meticulous in excess of 9 million deaths unanimously. Many researchers established that detecting cancer disease at early stages leads to an increase in probability to recuperate from cancer disease. In this proposed literature review work, we have chosen machine learning and also deep learning methods for cancer disease diagnosis in human body through algorithm based on issues, laboratory tests, imaging tests, biopsy, bone scan, computerized tomography (CT) scan, positron emission 240 tomography (PET), ultrasound images, etc. Moreover, we investigated how existing work analyzed cancer disease using recent technologies. The main objective of this state-of-art work is to evaluate performance by accuracy estimation on cancer disease prediction via machine learning. Furthermore, comparison of existing work specifies that how cancer disease were diagnosed, ways to prevent during early stage of cancer disease, or classification of disease by means of deep learning approaches were scrutinized, which makes cooperative in medical diagnosis synchronal relevance. The intention of this state of artwork is to afford investigators to choose to work in realizing machine learning as well as deep learning approaches for cancer disease identification.