Knowledge discovery from patient forums: gaining novel medical insights from patient experiences

Dirkson, A.R. (2022)

Doctoral Thesis

Patients share valuable advice and experiences with their peers in online patient discussion groups. These uncensored experiences can provide a complementary
perspective to that of the health professional and thereby yield novel hypotheses which could be tested in further rigorous medical research. This thesis focuses on the development of automatic extraction methods to harvest these patient experiences from online patient forums using text mining techniques. We also examine the complementary value of these patient-reported outcomes to traditional sources of medical knowledge for scientific hypothesis generation. Specifically, we focus on the extraction of adverse drug events (i.e., side effects) and coping strategies for dealing with adverse drug events.

• Natural language processing
• Text mining
• Information extraction
• Online patient forums
• Hypothesis generation
• Adverse drug events
• Coping strategies
• Gastrointestinal Stromal Tumor

• All authors: Dirkson, A.R.
• Supervisor: Kraaij, W.; Gelderblom, A.J.
• Co-supervisor: Verberne, S.
• Committee: Plaat, A.; Spruit, M.; Verspoor, K.; Hoogendoorn, M.; Poll, L. van de
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University
• Date: 2022-12-06
• Title of host publication: SIKS Dissertation Series
• Name: 2022-26