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Georgia Institute of Technology

Mobile Healthcare technologies for patients and providers

Georgia Institute of Technology via Coursera

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Overview

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This course aims to introduce senior undergraduate and entry-level graduate students to Biomedical and Health Informatics (BHI), focusing on informatics needs driven by Big Data in biomedicine and healthcare. Students will learn about health monitoring, clinical decision making, and the flow of clinical information. The course covers topics such as bioinformatics, imaging informatics, and health informatics, as well as basic knowledge in biostatistics, machine learning, data mining, visualization, and decision support. The teaching method includes lectures, examples from chronic condition monitoring, and clinical care. The intended audience for this course is students interested in mobile healthcare technologies for patients and providers.

Syllabus

This course intends to provide senior undergraduate and entry-level graduate students an introduction to Biomedical and Health Informatics (BHI) that covers: (1) informatics needs driven by Big Data generated from current biomedicine and health care (e.g., cancer, cardiovascular disease, aging population, etc.); (2) informatics challenges and common methodologies; and (3) progress made in BHI and opportunities.  

Health monitoring involves sensing, personal health records, and clinical decision making. The typical clinical process includes disease screening/diagnosis, treatment, and prognosis.  Using examples from chronic condition monitoring and clinical care, this course reviews the typical flow of clinical information, which includes the following steps: (1) data acquisition, storage, and curation; (2) data analysis, mining, and visualization; (3) modeling; (4) decision support; and (5) delivery (point-of-care access). Various introductory topics in bioinformatics, imaging informatics, and health informatics are organized as below:

  • Review of Basic Knowledge in Biostatistics, Machine Learning and Data Mining, Visualization, and Decision Support
  • High-Throughput –omic Informatics and Next-Generation Sequencing (NGS)
  •  Molecular and Cellular Imaging Informatics for Next-Generation Pathology (NGP)
  • Mobile Health and Health Informatics
  • Modeling for Systems Biology and Medicine

Taught by

May Wang

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