Inspired by his family’s medical background, master’s student Ishan Phansalkar is passionate about the potential of artificial intelligence to advance healthcare. The Indian Institute of Technology Bombay student recently completed his Australia India Research Students Fellowship at Monash University in Melbourne, where he harnessed AI to analyse clinical data. His work is part of a larger project that could support early detection of chorioamnionitis – a common cause of preterm birth. 

What led to your interest in artificial intelligence? I'm pursuing a Master of Technology in Artificial Intelligence and Data Science at the Indian Institute of Technology Bombay. Through university seminars and lectures, I discovered my passion for machine learning, a form of AI that employs data and algorithms to mimic human learning processes.

Growing up in a family of doctors, especially with my mother as a gynaecologist, has fuelled my interest in healthcare. Her work to improve the well-being of mothers and newborns has deeply motivated me. 

Can you tell me about your AIRS Fellowship project?
My project focused on the conversion of electronic health data into a more accessible and interoperable FHIR format to enable AI-driven analysis. The project can have a plethora of use cases, including but not limited to the early detection of chorioamnionitis – an infection of the placenta and the amniotic fluid. Chorioamnionitis is a common cause of preterm birth, a leading cause of death in children under the age of five. By using AI to analyse clinical data, including medical reports and patient surveys related to chorioamnionitis, one can provide more effective, targeted healthcare. 

My research is aimed at contributing to an ongoing project, ‘Targeted Delivery of Nucleic Acid Therapeutics for Preventing Preterm Birth’, led by Monash University in partnership with the University of Queensland and the University of Newcastle. This innovative project aims to address the issue of preterm birth by creating a targeted drug delivery system for the pregnant uterus to prevent premature uterine contractions. 

How did your collaboration with Australian researchers benefit your project? I collaborated with Monash University’s Central Clinical School as well as RMIT, both based in Melbourne. Under their expert guidance, I gained essential skills in data transformation and integration. The mentorship I received helped to broaden my perspective on health informatics and shape the direction of my research. The collaboration helped me get a taste of cutting-edge research at the global level, enabling me to expand my skillset for the future.

What were some memorable moments from your trip to Australia?
A highlight was the semester kick-off week. This event helped me to get to know the campus and connect with students from different backgrounds.

Engaging with faculty members, mentors, and fellow students offered a dynamic learning environment beyond the confines of the classroom. Our collaborative discussions, knowledge-sharing sessions, and informal interactions contributed to a holistic understanding of my subject area and fostered a sense of camaraderie within the academic community.