KAMAL Health
Project Overview
About
Language barriers and limited access to clinicians can delay early health assessment, particularly across South Asia and the Middle East. KAMAL asks focused follow-up questions in Arabic, Hindi, Urdu or English, using basic patient information to guide the conversation. It provides cautious, non-prescriptive guidance, flags urgent symptoms and converts each consultation into a structured report for a clinician. By supporting patients before an appointment, KAMAL could improve access, prompt earlier medical attention and help clinicians understand patients’ concerns more efficiently.
Team
Shubham Kumar Nigam
Dr. Shubham Kumar Nigam is a Research Fellow in the School of Computer Science at the University of Birmingham Dubai. His research focuses on responsible, multilingual and explainable artificial intelligence, with applications in healthcare and law. He currently works on KAMAL Health, developing patient-facing and clinical decision-support technologies that improve healthcare accessibility across languages. He completed his PhD in Computer Science and Engineering from IIT Kanpur and has published extensively in natural language processing, legal AI and trustworthy AI.
Piyush Patel
Piyush Patel is an undergraduate student studying Electrical Engineering at Madan Mohan Malaviya University of Technology,India. His core research interests lie in trustworthy machine learning, natural language processing, and the application of Large Language Models to improve healthcare accessibility. He has actively contributed to this field by co-authoring research on multilingual medical dialogue datasets, with work accepted at ACL 2026 workshops (BioNLP and MeLLM). Piyush is currently helping develop KAMAL, a multilingual patient-facing health assistant designed to bridge language barriers and provide equitable healthcare solutions through innovative AI.