Mr. Jyotipriya Das

Medical image data curation to train AI algorithms for disease detection and diagnosis

Abstract: 

The session is focused on exploring the criticality and benefits of data curation in developing medical imaging AI algorithms. Imaging systems and AI algorithms for disease detection and diagnosis are important in health care, ranging from MRI machines to CT Scanners. However the key factors to ensure data quality, accessibility, and usability, is the robust data curation pipeline to ensure the best quality data fed into the AI model development process which avoids wasting time and resources spent on data searches, compromised analytics, erroneous decision making, missed opportunities, and overall suboptimal performance. Although we advanced with different AI techniques, some issues related to data privacy make the research tough because it involves sensitive patient health related information.

Profile: 

With over 17 years of extensive experience in the IT and research industry, I have a distinguished career as an AI/ML Engineer in the Healthcare sector, based in New Jersey, USA. I have extensive knowledge in healthcare delivering different medical image processing algorithms in AI/ML. Currently holding a position of senior level AI/ML Engineer with excellent skills in medical imaging, leading the data engineering and MLOps to deliver cutting-edge solutions in image processing AI algorithms. Contributed several high impact research papers, international patents and published book on “Mastering Data Engineering and MLOps: Building Scalable Pipelines for AI-Driven Decision Making”. Received R&D 100 awards in 2022 and several Excellence awards on my current works.