Breast Cancer

8 July, 2020

According to OncoStem, breast cancer accounts for the 25% – 32% of all cancer types in India, thereby making it the most common cancer type in among the fairer sex. Every four minutes, one woman gets diagnosed with breast cancer, and one woman succumbs to it every thirteen minutes. Despite the advancement in curing procedures, there’s minimal improvement in the healing rate from the deadly disease. The main reason for this is the lack of an effective detection algorithm for breast cancer.


Machine Learning Comes to the Rescue

Since the last decade, three technologies are running all over the research labs, and they are data science, artificial intelligence, and machine learning. Among these, artificial intelligence has a lot to offer in the healthcare domain, but a lot of breast cancer specialists quote that in the field of breast cancer surgery, detection and treatment, machine learning will bring a revolutionary change. Since most of the people book an appointment, only after initial symptoms emerge, therefore the ML techniques mainly target to map the symptoms and their periods.


How Machine Learning Works as an Early-Stage Detection Tool

Machine Learning got the initial momentum after the introduction of image recognition and analysis techniques. In most of the healthcare data repositories, digital imaging and Radiology forms a significant part of diagnosis methodologies. Be it X-Ray or MRI; the imageries are an integral part of the diagnosis for the ailments. The Convolutional Neural Networks, which is a specially designed Machine Learning Architecture, does a similar job in a better way. The CNN Architecture is considered pixel-level data of imageries, accounting, and by evaluating the dots, lines, and curves. It has an upper edge above all the other types of conventional imageries as it can even detect and classify objects within the individual images. Breast cancer specialists also believe that the CNN mechanism can be further enhanced to predict the results of using the chemotherapy and immunotherapy on the patient.



Post Detection Utility of Neural Networks

Every time a new drug or a treatment procedure for treating breast cancer is developed, a lot needs to be done before actually using the methodology for curing purposes. However, ML and AI can together synthesize the data of the patient and create appropriate test cases and predict how the particular treatment course will work for the patient. Oncologists have observed that every time a woman comes to book an appointment for breast cancer detection, she is more concerned to know how she will be treated if she is diagnosed with breast cancer. With such a handy AI tool at hand, doctors can know before hand how the cancer treatment is going to work on a case to case basis by synthesizing the data of the patient in the Machine Learning Algorithm.

Overall, new technologies such as Machine Learning and Artificial Intelligence have given a lot of hope to the disease specialists as both the technologies have already contributed a lot to cancer detection and treatment methodologies.


Know Everything About Breast Cancer by Senior Medical Officer-Dr Indu Aggarwal

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