CHENNAI : Statistics show that about 40,000 women die in a year because of breast cancer, which is one in every 13 minutes a day. The importance of detecting the disease with the help of Artificial Intelligence is the need of the hour. Cautioning that breast cancer has become the most common disease among women both in the developed and the developing countries in the world in the past few years, Subash Kumar, a Computer Science Engineering graduate with around 12 years of experience in the field of data science, Artificial Intelligence machine learning- deep learning, from Chennai, claims that he has developed an easy way of detecting and curing the same.
The application of Artificial Intelligence (AI) machine learning technology with deep learning algorithms to whole-slide pathology images can potentially improve the diagnostic accuracy of breast cancer at a very early stage. Some scholars have assessed the performance of automated deep learning algorithms at detecting metastases in the tissue of women with breast cancer and compared results with pathologists’ diagnoses.
In the setting of a challenge competition, some deep learning a l g o r i t h m s achieved better diagnostic performance than pathologist’s results. In short, algorithm performance was comparable with an expert pathologist interpreting the whole-slide images without time constraints. “Hence, this experiment has shown that deep learning algorithms could identify the problem with accuracy.
This approach would significantly reduce the workload of pathologists and improve the management decisions on whether or not to administer therapy, perform a surgical intervention, etc. Overall, then, this interesting result shows the potential of Artificial Intelligence applied in cancer imaging for the detection of breast cancer tissues in women,” says Kumar. Kumar claims he has developed a simple machine-learning model using the University of Wisconsin data that is available in public for education capacity. This model predicts the presence of breast cancer with an accuracy of 91 per cent.
The continuous development of technology in the medical field will save countless lives and the overall quality of human life continues to improve over time, he says. He is presently working for USA’s government projects from Maryland near Washington DC. His areas of interest and research are machine learning, statistics and deep learning in the field of medicine. He has received an active membership from the world’s first and largest professional organisation dedicated to advancing cancer research called American Association for Cancer Research (AACA), for his contribution and research on identifying cancer using machine-learning methods. This membership is awarded to qualified scientists of any nation who have made substantial contributions to cancer research.