YoVDO

Mobile Healthcare technologies for patients and providers

Offered By: Georgia Institute of Technology via Coursera

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Health & Medicine Courses Bioinformatics Courses Data Mining Courses Machine Learning Courses Biostatistics Courses

Course Description

Overview

Explore mobile healthcare technologies for patients and providers in this comprehensive course. Gain an introduction to Biomedical and Health Informatics (BHI), covering informatics needs driven by Big Data in biomedicine and healthcare, common methodologies, and progress in the field. Examine health monitoring techniques, including sensing, personal health records, and clinical decision making. Analyze the clinical process flow, from disease screening and diagnosis to treatment and prognosis. Delve into data acquisition, storage, curation, analysis, mining, visualization, modeling, decision support, and point-of-care access. Study introductory topics in bioinformatics, imaging informatics, and health informatics, including biostatistics, machine learning, data mining, visualization, and decision support. Investigate high-throughput –omic informatics, next-generation sequencing, molecular and cellular imaging informatics for next-generation pathology, mobile health, and modeling for systems biology and medicine.

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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