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Developing Algorithms & Systems for Analytics

Developing novel algorithms and systems for big data analytics in healthcare

CDH has three major research foci: (1) Designing scalable pervasive healthcare monitoring, rehabilitation, and public health systems; (2) Building high performance networking and computing infrastructure for health data transmission and computation; and (3) Developing novel algorithms and systems for big data analytics in healthcare.
  • Two CDH members (Yu Cao and Benyuan Liu), were recently awarded a $1.3M NIH R01 grant, which aims to improve tuberculosis diagnostics using deep learning-based approaches and mobile health technologies among resource-poor and marginalized communities. In the second part of this research focus, we aim to develop an intelligent and scalable multi- modal medical analysis and retrieval system to support medical diagnosis, research, and teaching.
Our pioneer research is reshaping the future of the medical multimedia analysis and retrieval.
  • For example, CDH team member, Hong Yu, has developed innovative biomedical natural language processing and machine learning approaches. The proposed systems are publicly available and have been featured in Science, Nature, Journal Sentinel, and Neurobonkers.
  • On-going sample grants include:
    1. R01 HL125089-02 ($819,795) entitled “EHR Anticoagulants Pharmacovigilance”, which focus on the national priority area of anticoagulant adverse drug event (ADE) detection; and
    2. 5R01GM095476-06 ($490,160) entitled “Exploring natural language processing, image processing, machine learning, and user interfacing for intelligent biomedical figure search”.
Focused center-level efforts will enable the CDH team to fuse existing research strength to pursue much larger research grants and industry support.
  • In addition, CDH core team member, Jill Macoska, Director of the Center for Personalized Cancer Therapy (CPCT) is actively using RNAseq analysis to stratify patients for more targeted therapeutic approaches.