A review on neural networks approach on classifying cancers - Maha Mahmood; Belal Al-Khateeb; Wisam Makki Alwash (IAES International Journal of Artificial Intelligence (IJ-AI), 2020)
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 for medical practitioners to opt a proper treatment for cancer patients. Therefore, cancer cells should be identified correctly. Current developments in biological as well as in the computer science encouraged more studies to examine the role related to computational techniques in broad sphere regarding certain researches related to cancer. Using different AI approaches with regard to the disease’s medical diagnosis has been more general in recent times. Furthermore, there is more concentration on shown advantages of machine learning and AI methods. Cancer can be considered as one of the terrible diseases. Yearly, a lot of humans are dying from cancer. It is very essential for the practitioners of medical field to use suitable treatment regarding patients experiencing cancer. The data on cancer is specified as collection regarding thousands of genes. Thus, the cells of cancer must be properly detected. Currently, neural networks are considered as very significant area of research in the medical science, particularly in urology, radiology, cardiology, oncology, and a lot more. The presented work will survey different techniques of neural networks to classify lymph, neck and head, as well as breast cancer. The major goal of this work in the medical diagnostics has been guiding a lot of studies for developing user-friendly as well as inexpensive techniques, processes, as well as systems for the clinicians.