Through the course of the term, students will work on a term long project in 3 or 4-person groups.
The objective of each project is to leverage rich and high-quality datasets to answer and address open problems in the health domain. Project tasks can include data mining, modeling, prediction, classification, etc. but most importantly, projects should aim to advance the state-of-the-art in research literature or practice.
To get started, see strategies and resources for finding a research dataset.
A written report (this can be a publishable paper written to submit to a fitting venue or a report written strictly for this course). In either case, the paper should be written using a target venue's paper template and should follow the appropriate guidelines provided by a relevant journal/conference. See guidelines below.
A project website to document each project and progress. This website will serve as a final portfolio for the work that is done throughout the term. Some examples from previous terms are linked below:
Guidelines for Final Paper
ACM Transactions on Computing for Healthcare (ACM HEALTH)
Organization: Every manuscript must follow instructions provided by the selected venue. An example of submission guidelines for ACM HEALTH can be found here.
Template: All papers should use the appropriate template provided by the selected venue. An example of such a template for ACM HEALTH can be found here.
Reference Papers: It is always a good idea to have a few examples papers from the selected publication venue that can be used as a reference during the course of writing your own paper. Some example reference papers for ACM HEALTH can be found here.
LaTex: All final papers should be written using LaTex. Each project team should use Overleaf - an online, collaborative LaTex editor.
There will be several milestones to track progress of the project throughout the term:
P1 (7%): Exploratory & Initial Analysis (~week 3)
P2 (8%): Introduction & Related Work (~week 4 - 5)
P3 (13%): Method & Initial Results (~week 6 - 7)
P4 (22%): Final Presentation & Final Paper (week 9)
P1 (7%) - Exploratory & Initial Analysis
PTSD Detection with Speech Audio (Spring 2022)
P2 (8%) - Introduction & Related Work
This assignment is the first milestone toward writing your own research paper for your course project. Regardless of whether your team plans for a publishable paper or class report, this paper should be written using the appropriate template for a journal/conference in the space. See the Guidelines for the Final Paper for additional instructions.
Write the Introduction & Related Work sections (~2 pages) of your research paper for your course project.
Guidelines on items to address are below:
Why is the problem space important?
What specific gap exists in the space?
Describe related work in the space (~ 8 or more other papers that attempted to address the identified problem or similar problems in the space?
What is your own research objective(s)?
Provide a brief description (1 - 2 sentences) of how you plan to accomplish the stated objectives.
What are the key contributions of your work?
Numbers 1 - 3 above must be supported with references.
If writing a research paper is new to everyone in your project group, please reach out to the teaching team for additional guidance. We would be glad to help!
P3 (13%): Method & Initial Results
In this assignment, you will continue with implementing data science methods toward your project objective/goal. Then you will write the methods and results section of your paper (continuing with the template you used in P2).
Write clear and clean code (in python using jupyter notebook/google colab) with appropriate comments and section titles to implement methods toward your project objective/goal.
Upload the written code and any supporting items in your github repo under a cleared named directory (e.g. P3 - Method & Results).
Write the methods and results section of your project report/paper. See guidelines for writing each section below.
Submit a .pdf of your paper on canvas.
P4: Final Presentation (7%)
The final presentations will be on Tuesday (11/8) and Thursday (11/10) during our regular class time. All presentations should be 15mins long with 5mins for Q&A.
The presentation should include the following:
Motivation/Background (why should the audience care?)
Research objective (what is the specific goal of the work? why is it important?)
Data Description/Summary (use text and visuals - this is a good place for some of your exploratory analysis)
Methodology (think flowchart if there are multiple steps, give grounded rationale for the approach taken)
Results (key findings/takeaways)
Limitations/Challenges (including how you would address these in future work)
Top learnings from the project experience
References (on appropriate slides)
Things to consider:
The grading scaling is as follows: A+ (100%), A- (94%), B+ (88%), B- (82%), C+ (76%), C- (70%), Less than C-.
You are the authors of the paper, the researchers behind the work, the experts on the topic. Make sure to present accordingly.
You are not graded based on whether you achieved good/bad results. Instead, you are graded on the soundness of your approach, knowledge of the space, and ability to communicate the work.
Use good presentation practice (for example: slides should not be too busy with text and/or visuals, figures should be legible with clear axis labels and legends, etc.)
There is a strict time limit. It's a good idea to practice your talk before hand.
Have fun!!! If you're not enthused talking about your own work, then chances are the audience is not enthused listening.
Presentation order is TBD.
P4: Final Paper (15%)
The final paper is due on Friday (11/11). This should be a fully polished version that includes revisions based on comments received in prior submissions and other improvements that your team has identified.
The final paper should include sections for introduction, related work, methods and results per P3 & P4. In addition, this version should have a newly added discussion section. The discussion section should include implications of your results/findings, comparison with results from related studies, limitations of the work presented, and directions for future research.
As you finalize your paper, be sure to leverage examples such as this one or other examples listed under P3.
Update your project website to tell the full story of your project and findings. Be sure to include your final paper, final presentation slides, and a link to your github repo with the final version of your written code (which must be well organized and commented).
Submit a link to your project website as a comment on Canvas
Submit a pdf of your final paper on Canvas
Note: It is encouraged to ask for input from the teaching team as you finalize your project and paper. While we won't read your full paper before submission, we can read a short sections and/or provide input on how to make the analysis and/or written presentation strong.