MACHINE LEARNING IN HEALTH
You should use and summarize 20 or more peer reviewed articles published in the last 10 years.
You should use a citation manager such as Zotero or Mendeley
HLST 3350: Health Data Analytics, Machine Learning and AI
A brief overview of the topic and its relevance in healthcare. Here are some guiding questions.
What is the problem (history, global view, Canadian view)?
Who is interested in solving the problem (stakeholders)?
Why are they interested to solve the problem?
What kind of solutions exist to solve the problem (if any, if not state it clearly)?
Why was machine learning used? What are the expectations (faster solutions, more accurate solutions, …)?
Results of the Literature Review (50 points)
The following questions are for guidance only, you may organize this section the way you want based on your readings.
Research questions and perspectives: Discuss the research questions and perspectives that you’ve found in literature.
Research settings: What are the different settings used (rural s urban, healthcare facilities vs. community centers, medical perspective of health vs. social perspective, etc.?
What are the algorithms used and what were the results?
Are these results comparable (same population, same setting)?
Which approaches/algorithms yield to a better result?
Compare the results of the different studies.
Impact
Discuss the advantages and impact of machine learning solutions that arise from literature review.
Discuss the shortcoming, challenges and limitations that arise in literature
Suggest a research project that approach the topic in a new way (e.g. using an emerging technology) or that tackles untapped parts of this topic (you may rely on the challenges and limitations you’ve observed in your literature review to develop your research perspectives)
Discuss any limitations of your term paper.
