Abstract: We will discuss various applications of machine learning in the healthcare sector. After an introductory review covering applications from across the field, we will describe our recent work on predicting the birth weight of a fetus from ultrasound measurements (collaborative work with Uma Ram, obstetrician/gynaecologist; C Kumari, GI Menon, L Narlikar).  We will also discuss the problem of data sharing and patient confidentiality in medicine, and describe one possible alternative, sharing synthetic data generated to mimic essential characteristics of real data. We will describe an algorithm, MMMSynth, for this, which outperforms deep-learning-based algorithms (with C. Kumari).

About the Speaker: Dr. Rahul Siddharthan is a Professor of Computational Biology at the Institute of Mathematical Sciences (IMSc), Chennai. His research interests include bioinformatic algorithms, regulatory genomics, chromatin, evolutionary biology, and, more recently, machine learning and clinical outcomes. He earned his Ph.D. in Physics from the Indian Institute of Science, Bangalore, and transitioned into biology during his second postdoctoral fellowship at The Rockefeller University, New York. He was a postdoctoral fellow at École Normale Supérieure (ENS), Paris (2000–2002), and subsequently at Rockefeller University (2002–2004). Dr. Siddharthan joined the Physics group at IMSc in 2004, and in 2013, they established a new research group and Ph.D. programme in Computational Biology.

Looking forward to your active participation.