Clinical, Health, Medical Informatics

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 (Electronic Health Records, radiology reports, pathology 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. Prasath Lab is interested in harnessing recent Large Language Models (LLMs) from GPT to LLaMA for extracting valuable insights from diverse medical texts across the healthcare system. From EHR, biomedical databases to scientific literature (PubMed,...), our aim here is to decode complex medical narratives and uncover hidden knowledge and help healthcare practitioners, medical professionals in decision making/augmentation.

We are also part of multiple collaborative efforts and our research interests span the full spectrum of clinical, health and medical informatics:

• Large Language Models (LLMs)

• GPT and Variants

• xAI Applications in Text Data

• Generative AI for NLP

• Interpretable AI Tools

• Multimodal Fusion (text, imaging, genomics,...)

• Foundation Models

Selected publications:

• S. Rawat, V. Vijayarajan, V. B. S. Prasath. Modified K-means with cluster assignment - Application to COVID-19 data. arXiv, February 2024. doi:10.48550/arXiv.2402.03380

• M. Imam, S. Hamzah, S. Aggarwal, S. Dev, V. B. S. Prasath. On utilizing transformer-based models for preventing harmful response in LLMs. Submitted, 2024. 

• P. Rajdeo, B. Aronow, V. B. S. Prasath. Breaking new ground in biomedical AI: Harnessing data to boost LLM capabilities with a superior hybrid RAG pipeline. In preparation, 2025.

• V. B. S. Prasath. Leveraging large language models (LLMs) for conversational nutrition guidance – Opportunities and challenges. In preparation, 2025.

• L. Ferreira, R. Hopkin, V. B. S. Prasath. ChatGENE. In preparation, 2025.