cff-version: 1.2.0
abstract: "<p>The research objective of this thesis is to bridge the gap between human and machine intelligence in the interpretation of colorectal cancer patient experiences extracted from patient web forums. This Computer Science thesis was done in collaboration with colorectal cancer human experts from Erasmus MC. To perform this scientific research and make these human experts and GPT-3.5 interpret colorectal cancer patient experiences, nearly 300k patient web forums were scraped from the American platform called <span style="color: rgb(33, 33, 33);">Cancer Survivors Network USA (</span><a href="https://csn.cancer.org/categories/colorectal" target="_blank">Colorectal Cancer — Cancer Survivors Network</a><span style="color: rgb(33, 33, 33);">). For extracting the patient web forums, the </span>Selenium webdriver was used to extract the page urls for each discussion thread, and BeautifulSoup4 (bs4)&nbsp;was used to access the page urls and parse the html elements from each type of patient forum, including main post, comment and reply, and store them in a local dataset. The patient forum attributes stored in the dataset are: URL – username (i.e. author of the post)– userposts (i.e. number of posts written by the author)– time (i.e. when the post was made)– title – post (i.e. text consisting of unstructured colorectal cancer patient experiences)</p>"
authors:
  - family-names: Patandin
    given-names: Ayush
title: "Data supporting the thesis “Exploring Hybrid Intelligence for Topic Interpretation in Colorectal Cancer Research: A Comparative Study of GPT-3.5 and Human Expertise”"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/a7e63b3f-18f5-4ae4-8750-255528f82178.v1
license: CC0
date-released: 2023-09-04