.India is actively ensuring a digital health ecological community to support its own journey for universal healthcare. Quality-graded health information can offer phenomenal decision-making assistance in this effort. The largest obstacle to creating artificial intelligence (AI)- enabled healthcare innovations in India is actually the schedule of high-grade annotated data for South Asians, especially Indians, that could be made use of to qualify and also verify artificial intelligence applications.The large swimming pool of multimodal data collected during the course of client treatment experiences or disease-specific security gives distinct archival opportunities for big medical datasets. When annotated, clinical pictures including X-ray, electronic tomography (CT), magnetic vibration imaging (MRI), ultrasound examination, as well as whole-slide graphics acquired in the course of an individualu00e2 $ s visit to healthcare organizations are an abundant information for instruction AI algorithms. Such ventures consist of the Clinical Image resolution Databank of the Valencia Area, PathLAKE, The Cancer Cells Image Resolution Archive1, as well as the Medical Artificial Intelligence Information for All initiative2. Some of the existing health care image resolution datasets from India are actually the IN-CXR (an open dataset of trunk radiography for tuberculosis), the Indian Diabetic Retinopathy Photo Dataset (IDRiD) 3, Chu00c3 u00a1 ku00e1 u00b9 u20a4 u (a glaucoma-specific fundus image database4), and CHAVI-RO (an extensive digital older post of cancer cells imaging from radiation oncology5). Having said that, India has no centrally collaborated as well as discoverable repository for health care imaging records along with well established interoperable specifications.