IISE Data Analytics and Information systems division (dais) student data analytics competition

The Data Analytics Competition is an annual student competition event organized by the Data Analytics and Information Systems (DAIS) division of the Institute of Industrial and Systems Engineers (IISE). The main objective of the competition is to provide the students with the opportunity to learn, showcase, and enhance their data analysis and visualization skills through working with real-world problems with real-sized data sets.

Problem Description

(link to paper):

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, with incidences doubled over the past two decades due to increasing risk factors. Despite surveillance, the majority of HCC cases are diagnosed at advanced stages that can be treated only using (Transarterial chemoembolization) TACE, or systemic therapy. TACE failure can occur in 60% of patients receiving the procedure, with subsequent financial and emotional burdens. Radiomics has emerged as a new tool capable of predicting tumor response to TACE from the pre-procedural CT study.

This dataset retrospectively acquired data collection includes pre- and post-procedure CT imaging studies of 105 confirmed HCC patients who underwent TACE between 2002 and 2012 with an available treatment outcome, in the form of time-to-progression and overall survival. Baseline imaging includes multiphasic contrast-enhanced CT with no image artifacts (e.g. surgical clip) and was obtained 1-12 weeks (average 3 weeks) prior to the first TACE session. Semiautomatic segmentation of liver, tumor, and blood vessels created using AMIRA was manually clinically curated. These segmentations of each pre-procedural CT study were done for the purpose of algorithm training for prediction and automatic liver tumor segmentation.

Two datasets will be provided for this competition:

  • Pre- and post-procedure CT images in the format of DICOM-Seg. We suggest the participants use the latest stable version of 3D-Slicer for data visualization after installing the “quantitative reporting” extension. Step-by-step installation and guidance can be found in: https://qiicr.gitbook.io/quantitativereporting-guide/
  • A table of clinical data with descriptions.
  • The participants of this case study competition are required to complete the following tasks:
    Specific Task: Please segment the tumors from CT images.

Eligibility

  • Individuals or teams of a maximum of four members.
  • Student members can be undergraduate or graduate students from higher education institutes in the field of Industrial & Systems Engineering or related fields.
  • Student members should be enrolled at the time of the submission of the proposal.
  • At least one of the team members must be an active member of the Data Analytics and Information System (DAIS) division of IISE.
  • A team must submit a notice of intent to participate in the competition.

Competition Process

Notice of Intent

A team must submit a notice of intent to participate in the competition via email to the chairs of the competition steering committee by Friday, Jan. 26, 2024. The notice of intent needs to include:

  1. The list of names of team members, their affiliations, and contact information (email and phone).
  2. One team member is identified as the main contact.

The competition chairs will share the description of competition challenge questions and data set through email to the main contact provided by the team on Friday, Feb. 2, 2024.

Submission of the Results

Participating teams or individuals are required to submit a single compressed file that includes 1) a final report, and 2) the source code and scripts via email to the chair of the competition steering committee by Friday, March 1, 2024. The competition steering committee will evaluate the submissions, and a maximum of top four teams will be selected as finalists. More details about the submission guidelines and review criteria will be released along with the competition challenge questions and data set.

Final Presentation

The selected finalist teams and individuals will present the model motivation, model approach, and results at the 2024 IISE Annual Conference & Expo, May 18 – 21, 2024 Montreal, Canada. More information on the presentation contents will be provided to the finalist teams.

Evaluation Process

Approval of the Notice of Intent

The competition steering committee will review and approve or reject the submitted notices of intent to participate based on the eligibility criteria. Approval emails will be sent together with the competition challenge questions and dataset by the chair of the committee by Friday, Feb. 2, 2024.

Selection of Top Finalist Teams

The competition steering committee will select a maximum of four finalist teams. Finalist teams will be notified by email by the chair of the committee by Thursday, March 8, 2024.

Selection of Winners

The selected finalist teams will present their results in 2024 IISE Annual Conference & Expo, May 18 – 21, 2024 Montreal, Canada. A blind vote cast by invited judges will decide the winner after the presentations.

Recognition

  • Recognition at the Annual Conference:
    • at the DAIS Town Hall Meeting
  • Certificate provided by IISE (either mailed or given at the town hall meeting) for the 1st prize winners.
  • 2nd and 3rd prize winners will receive a digital certificate.
    Recognition in ISE magazine
  • Recognition on DAIS webpage and in the newsletter

Important dates/deadlines

  • Notice of Intent: January 26, 2024 
  • Notice of the team approval: February 2, 2024 
  • Competition challenge questions are made available: February 2, 2024 
  • Deadline for submission of the results: March 1, 2024 
  • Notification to the finalist teams: March 24, 2024 
  • IISE Annual Conference & Expo: May 18-21, 2024 

Competition Chairs

Xiaoyu Chen, University at Buffalo, SUNY
Yinan Wang, Rensselaer Polytechnic Institute

2024 Winner

1st Place
Haixu Liu, Zerui Tao, Wenzhen Dong, Qiuzhuang Sun
The University of Sydney

2023 Winner

1st Place
Chengyu Tao, Xuanming Cao, Peng Ye, Juan Du (advisor)
The Hong Kong University of Science and Technology

Questions, contact Amy Straub at IISE.

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