Clinical, Health, Medical Informatics

Machine Learning for applied clinical informatics - To Be Added

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 data, Critical Care, Emergency Medicine, Sepsis, Bronchopulmonary Dysplasia. Healthcare NLP/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.

Project pages:

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

  2. EHR : RareDiseases, ASD

Selected publications:

  • 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]

  • 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]

  • M. Shah, D. Jain, V. B. S. Prasath, K. Dufendach. Artificial intelligence in bronchopulmonary dysplasia - Current research and unexplored frontiers. Submitted, 2022.