Clinical, Health, Medical Informatics
Machine Learning for Applied Clinical Informatics
Application of natural language processing, signal processing, image processing, computer vision and machine learning techniques to clinical, heath, and medical informatics problems. AI for NICU/PICU/ICU/CICU data, Critical Care, Emergency Medicine, Sepsis, Bronchopulmonary Dysplasia. Healthcare NLP for EHR/EMR/ePHI/PHR/PRO Data - Unstructured text data analysis with ML/DL - Clinical data - MLDevOps + FHIR. AI for Healthcare and Clinical Implementation. AI for NICU/PICU/ICU/CICU. mHealth, IoToys in pediatrics.
EHR : RareDiseases, ASD
Others: CPIID, mHealth
AI Text Analytics
Natural language processing (NLP) is becoming commonplace and in the last few years large language models are increasingly used in processing various types of data (EHR, radiology reports,...). Hence personal genomes will be increasingly utilized for precision medicine. It is therefore very important to develop new approaches using latest data science tools for solving problems in bioinformatics. Prasath Lab is interested in leveraging AI/ML/DL to solve challenges in large-scale text processing in the clinical informatics domain. Given the expertise and experience with the multidisciplinary projects and the proven track-record in bringing quantitative approaches from mathematics, computer science, and statistics we are well-poised to be a connector among different domains. We are also part of multiple collaborative efforts and our research interests span the full spectrum of informatics: