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.


Project pages:


  1. AI/NLP/Imaging for NICU: NLP-PICC, PICCLineNet, BPD, Sepsis, NPD

  2. EHR : RareDiseases, ASD

  3. Others: CPIID, mHealth


Selected publications:


  • M. M. S. Missen, A. Javed, H. Asmat, M. Nosheen, M. Coustaty, N. Salamat, V. B. S. Prasath. Systematic review and usability evaluation of writing mobile apps for children. New Review of Hypermedia and Multimedia, 25(3), 137-160, December 2019. Special issue on Advances in Multimedia and Educational Technology. doi:10.1080/13614568.2019.1677787

  • M. Shah, D. Shu, V. B. S. Prasath, Y. Ni, A. Schapiro, K. Dufendach. Machine learning for detection of correct peripherally inserted central catheter tip position from radiology reports in infants. Applied Clinical Informatics, 12(04), 856-863, August 2021. doi:10.1055/s-0041-1735178 [NLP-PICC]

  • M. Shah, D. Jain, V. B. S. Prasath, K. Dufendach. Artificial intelligence in bronchopulmonary dysplasia - Current research and unexplored frontiers. Pediatric Research, 2022. doi:10.1038/s41390-022-02387-z

  • Prasath et al., PICCLineNet: Deep learning for detecting peripherally inserted central catheter (PICC) lines and tips from radiological images in infants. 2022. Preliminary version at arXiv:22xx.abcde. [PICCLineNet]

  • Prasath et al., Challenges of heterogenous data standardization and organization - An informatics perspective. 2022. In preparation.