Diagnosing cancer at an early stage increases the chance of performing the effective treatment in many tumor groups. Key approaches include screening patients who are at risk but have no symptoms and rapidly investigating those who do. Machine Learning algorithms have shown a profound potential to revolutionize early cancer diagnosis.  

In relation to cancer awareness month, INDIAai organized an insightful conversation with Geetha Manjunath, Founder, CEO and CTO of NIRMAI, a startup that uses AI and ML for early breast cancer detection. The LinkedIn live was hosted by Jibu Elias, Content & Research Lead at INDIAai. 

AI has a significant role in every stage of cancer care, from its detection. “The stage one detection of breast cancer has a 95% of survival rate,” said Geetha Manjunath, speaking about the role of AI in early cancer detection. 

If an individual is detected with cancer, AI can aid in treatment planning based on each patient’s needs, which acts as a helping hand for the doctors. Even after the complete cure, cancer is a disease which tends to return. Therefore, the patient will have to undergo regular checkup-. This is yet another area AI can help in. “My favorite is when AI plays the role of a mini robotic doctor”, she added. 

Enhancing awareness 

 A lack of awareness about breast cancer is persistent in rural areas, where there is a shortage of hospitals and qualified doctors. However, point-of-care devices can tackle this issue. 

 These devices can be installed in primary care centers. The health workers of these centers should be trained on the usage of the device. The AI-enabled device will generate the report within 15 minutes and detect if the person requires further care. 

 “When we do this in every village, the screening process can bring a big change in the field of cancer”, says Geetha Manjunath.

Cost of diagnosis 

 Cancer care and treatment are very costly processes. Using AI tools as a second opinion can also reduce the money spent on cancer care. 

 Similarly, using AI in the process of diagnosis can reduce the time consumed for result generation. Even one or two weeks of early detection can reduce the overall expense. AI can also be used for drug development, precision medicine many more. 

Diagnosing with AI 

AI tools such as thermalytix can be used to analyze thermal images. The changes that occur during the abnormal growth of a cell can be extracted using thermal images. Thermal images are the mapping of temperature distribution on the chest. Every temperature is identified using colors.

 “It is very difficult to visually analyze Thermal images”, says Geetha Manjunath. So Thermalytix uses AI to diagnose any abnormality in these thermal images, thereby enabling cancer detection to be faster. Different scores are generated based on the level of abnormality. 

Fear of AI 

The fear of radiologists being replaced by AI is common. Similarly, some fail to accept AI functions stating it will never match human intuition. 

“Radiologists using AI will replace radiologists not using AI”, stated Geetha Manjunath, addressing the common fear of AI. 

AI has the potential to make a huge social impact. It should not be used for every problem. It is important to remember, the result of AI can affect a life. 

Watch the LinkedIn Live here.