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MED264: Principles of Biomedical Informatics

Instructor:  Tsung-Ting Kuo, PhD,

Teaching Assistants: Jihoon Kim (j5kim@ucsd.edu) and Jonathan Lam (j7lam@ucsd.edu)

When:  Fall 2021 -- Courses will be offered fully remote on Mondays from 3:30 to 5:30 pm and Thursdays from 1:30 to 3:30 pm.

Office Hours: by appointment

Course Objectives: The purpose of this class is to provide an engaging and lively introduction to the field of biomedical informatics. Building up from the basic bits of data to modeling complex organisms and organizations, the course will explore the nature of biomedical information and how this information is and can be used in the care of individual patients and populations. We highlight practical and state-of-the-art technologies in biomedical informatics to get students exposed to the current healthcare research environment. 

 

MED264 Syllabus

DATE

SPEAKER

SESSION TITLE

09/23

Tsung-Ting Kuo and Lucila Ohno-Machado

Introduction to Biomedical Informatics, Decision Making, and this Course

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BLOCK 1 - Clinical Informatics

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09/27

Tsung-Ting Kuo

Introduction to Machine Learning in Biomedical Informatics

09/30

Jonathan Lam

A Practical Introduction to Machine Learning with Python

Skill Assessment Due

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 10/04

Alexander Wenzel

Basic Experimental Design and Basic Statistics with R

Teams Formed for Final Project

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10/07

Jejo Koola

Evaluating Predictive Analytics for Clinical Decision Support

10/11

Robert El-Kareh

The Big Picture of Informatics Implemented in Medical Centers and Introduction to EPIC

10/14

Sally Baxter

Introduction to Ophthalmology informatics and All-of-Us

10/18

Chris Longhurst

Informatics Innovations at the Bedside and Beyond: Mobile Health, Applications linked to EHR systems 

 10/21

Amy Sitapati

Population Health Informatics

Project Proposal Due

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10/25

Jihoon Kim

Advanced Statistics/Biomedical Informatics with R

 10/28

Shamim Nemati

Deep Learning and Predictive Analytics in the ICU

Graded Proposals Returned

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11/01

Rodney Gabriel

Anesthesia Informatics

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BLOCK 2 - Clinical Research Informatics

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11/04

Michael Hogarth

Not All Data are Structured: Clinical Natural Language Processing and Standards

11/08

Nigha Nyugen and Mary Linn Bergstrom

Evidence-Based Decision Making / Systematic Reviews

11/11

Veterans’ Day

NO CLASS

11/15

Tsung-Ting Kuo

Biomedical, Healthcare and Genomic Blockchain Applications

11/18

Michael Hogarth and Reid Otsuji

Relational Models and Data Systems / Introduction to SQL

11/22

Kai Zheng

Human Factors: Workflow Optimization and Human-Computer Interaction 

11/25

Thanksgiving

NO CLASS

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BLOCK 3 - Bioinformatics

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11/29

Hannah Carter

Systems Biology for Biomedical Discovery

12/02

Kathleen Curtius

Cancer Genomics and Evolution

 

Project Report Due

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12/06

Final Presentations from Student Teams

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Course grades will be based on:

  1. Proposal (20%)
  2. Homework (30%)
  3. Final project participation and report (50%)
  4. Bonus credit for course participation and submitting evaluation forms (10%, 0.5% per lecture)