Hospitals kickstart efforts to test AI for cancer detection
Experts say tech still nascent, diversified dataset for correct risk profiling currently unavailable
The development of artificial intelligence (AI) models in oncology and radiology for early cancer detection is gradually gathering steam, with several Indian health care companies initiating research studies to integrate them into screening efforts.
Apollo Cancer Centre recently inaugurated India’s first Ai-driven precision oncology centre in Bengaluru. This centre is working on providing precise and timely oncology care, leveraging AI for accurate diagnosis, insights, cancer risk assessment, and treatment protocols. Similarly, Apollo Radiology International announced its tie-up with Google recently to develop AI models for the early detection of cancer.
Improved study of scans
Speaking on the potential role of AI in oncology, Joydeep Ghosh, senior consultant medical oncologist at Apollo Cancer Centres, Kolkata, said that AI algorithms can scrutinise radiological scans, such as mammograms (for breast cancer) and computed tomography and positron emission tomography scan images (for lung cancer), detecting subtle abnormalities that may indicate the presence of cancer at its nascent stage. “This early identification, in turn, will enable doctors to initiate timely interventions, significantly enhancing the chances of successful treatment and recovery,” he added.
AI algorithms can analyse vast datasets, including genetic information and patient histories, to identify genetic markers and risk factors associated with specific cancers. AI models are being used for tuberculosis (TB) screening.
An example is Qure.ai, a Mumbai-based startup, which has been providing its AI algorithm-based device for TB screening to several health facilities since February 2020.
Commenting on the uptick in the adoption of AI models, Ghosh said that some centres are in the process of incorporating AI into mammography reporting for breast cancer, but it is too early to make it standard practice.
AI models still a trial-and-error-based method
Despite advances in AI algorithms, doctors acknowledge that it is still in its infancy as a diagnostic tool, as the development of successful AI models may still take a long time.
Nitesh Rohatgi, senior director of medical oncology at Fortis Memorial Research Institute, said that one of the biggest issues with integrating AI models with cancer detection would be data collection. “AI algorithms require a diversified dataset for correct risk profiling of potential cancer patients, which currently is not available anywhere in the world,” he said.
Terming AI as a trial-and-error method, Aparna Dhar, director of hereditary, precision oncology and genetic counselling at Max Super Specialty Hospital, Delhi, said that while AI capabilities can improve the accuracy and speed of cancer diagnosis, one must understand that there can always be a blind spot due to a lack of data.