AI-powered analysis of multiparameter flow cytometry data for Indian clinical laboratories
Under the leadership of Dr. Rama Akondy (Department of Biology) and Dr. Debayan Gupta (Department of Computer Science), researchers are developing an AI-based approach for analysing flow cytometry data.
Flow cytometry, a widely used laboratory technique, allows for the simultaneous analysis of multiple cellular properties. While essential in immunology research, it also serves as a diagnostic tool for conditions such as hematologic malignancies. However, diagnosis currently relies on manual interpretation by clinical pathologists, requiring specialised expertise and time-intensive analysis.
By integrating AI-based methods, this project seeks to enhance the speed, objectivity, and efficiency of flow cytometry analysis while also uncovering novel disease patterns and associations. This approach has the potential to transform diagnostic processes, making them more precise and accessible.
