Artificial Intelligence in Oncology: Transforming Cancer Care in India

Artificial intelligence (AI) has entered almost every field imaginable — and oncology is no exception. Yet, the excitement surrounding AI often oscillates between utopian promise and dystopian fear. In India, where oncologists face overwhelming patient loads and resource limitations, AI may not replace human expertise — but it can certainly amplify it.

From Diagnosis to Decision: Where AI is Already Making a Difference

AI tools are now being integrated into pathology, radiology, and genomics — areas that generate enormous amounts of data. Algorithms trained on thousands of scans can help detect lung nodules, breast lesions, or abnormal lymph nodes with remarkable accuracy. In pathology, digital slides and AI-based image recognition are speeding up diagnosis while minimizing human error. Meanwhile, in molecular oncology, AI helps identify driver mutations and treatment targets by analyzing genomic data faster than any human can.

In India, where manpower and infrastructure remain limiting factors, these tools are not just convenient — they’re transformative. AI-assisted mammography screening programs in rural areas are helping bridge the radiologist gap. Companies like Niramai and Qure.ai have already deployed AI solutions that make cancer detection more accessible and affordable.

The Promise and the Paradox

But every revolution carries risk. AI systems are only as good as the data they are trained on. If most algorithms are developed using Western datasets, how accurately will they perform for Indian patients — whose genetic backgrounds, disease biology, and imaging quality differ? This “data divide” risks introducing new biases into cancer care, potentially widening existing inequalities.

Another paradox lies in implementation. Many hospitals adopt AI tools without clear validation, or worse, use them as marketing buzzwords rather than clinical aids. The true test of AI is not how smart it looks on paper, but how much it improves patient outcomes in the real world.

The Ethical Equation: Augment, Not Replace

Dr. Bishal Gyawali often argues that innovation must be judged not by novelty but by necessity. The same holds true for AI. We do not need more algorithms predicting progression-free survival with fancy curves — we need AI that helps an overburdened oncologist in a district hospital decide the right chemotherapy for the right patient, at the right cost.

Ethical deployment of AI in India must therefore focus on augmentation, not automation — helping doctors make better decisions, not making them redundant. Transparency, validation in local contexts, and cost-effectiveness should be built into every AI rollout plan.

The Road Ahead

AI will not cure cancer — but it can help cure the inefficiencies that surround cancer care. India, with its massive patient data and growing digital infrastructure, is uniquely positioned to lead in this space — if it invests in responsible innovation. The challenge is to ensure that the future of oncology is both intelligent and inclusive.

Technology may transform healthcare delivery, but compassion, judgment, and context will always remain human. The best oncologists of tomorrow will not compete with AI — they will collaborate with it.

— Dr. Amol Akhade | Fortis Cancer Institute Mumbai@SuyogCancer