Hyderabad: Generative artificial intelligence is no longer confined to tech demos or language models; it is finding its place in healthcare and diagnostic labs. A recent article by Prof. S. Bapi Raju of the International Institute of Information Technology (IIIT), Hyderabad, reveals how GenAI can create new content such as radiology reports, synthetic images for rare diseases, and summaries of medical literature which is more than its perceived capability of processing data.Models trained to classify images, detect tumours, segment organs, and predict health outcomes are now part of medical workflows. However, GenAI goes a step further by generating new data and content that can supplement existing information.The article states that such systems help ease the pressure on overburdened medical professionals. GenAI tools like CheXagent, for instance, can analyse chest X-rays and give probable findings. But these tools aren’t flawless. When tested on Indian datasets, the system sometimes confused harmless artefacts for signs of disease. “Results (a) are in line with the ground truth. However, in (b), image artefacts are being mistaken as calcified granuloma, and the resulting report is erroneous,” Prof Raju states in the article.Further, he brings forth a deeper concern of the imbalance in where medical data comes from. Urban hospitals have digital systems in place, but rural healthcare centres lack such records. “Such skewness can potentially introduce urban bias into models,” he warns. The article argues that India needs its own large-scale datasets, similar to what MIMIC and UK Biobank offer abroad. Building such repositories could help reduce inaccuracies and make AI tools more reliable for Indian patients.He adds that GenAI’s full potential will be realised only if we solve the practical and technical issues like bias, limited datasets, inconsistent imaging, and lack of validation standards. “By addressing key obstacles and ensuring responsible AI adoption, we can fully harness the power of GenAI to improve patient outcomes and revolutionise modern medicine,” he concludes.