7th International Conference on ICTCS 2022

Authors - Ruheena Hashmi Syed Mubeen Hashmi, Dnyaneshwari D. Pati, Anjali A Rokde
Abstract - Cancer is among the major killer diseases that result from the accumulation of genetic mutations and hence need early detection before it develops in the body. There are 200 different types of cancer in the human body system, such as lung, breast, prostate, skin and hematologic cancer. Health practitioners and scholars confirm that contemporary cancer screening methods are ineffective. The most commonly applied detection methods are mammography, ultrasound, biopsy, MRI, and CT scan. Experts have argued that existing techniques rely on the tumor’s physical properties and appearance, which render them ineffective. Therefore, efficient, reliable and accurate measures for cancer treatment (detection and medical diagnosis) and prevention are urgently needed. An advent and emerging technology is AI, a part of Artificial Intelligence that utilizes an assortment of factual, probabilistic and improvement procedures that permits PCs to "learn" from past models and to recognize hard-to-observe designs from huge, uproarious or complex datasets. Single-cell RNA sequencing data in the proposed system are used to detecting breast cancer gene expressions. ML classifications are used to diagnosis and prediction of breast cancer, such as support vector machines (SVM), Random Forest (RF). K-nearest neighbours (K-NN), Decision Tree (DT) these classifiers are to break down highlight extraction to recognize the harmless and threatening cancers of the BC (Breast cancer).