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299P Integrating artificial intelligence (AI) into oncology clinical trial matching: Preliminary insights from Canadian simulated and retrospective data

Year: 2025
Type: article
Abstract: AI-assisted clinical trial matching systems (CTMS) have shown promise in streamlining patient screening, where eligibility criteria are complex and manual review is resource-intensive. Building on recent natural language processing (NLP)-based models demonstrating high accuracy (Wang et al. 2024), a CTMS combining MLP with rule-based eligibility was piloted to support the Canada-wide Clinical Trials Navigator (CTN) program, to improve trial matching in breast and colorectal cancer.
DOI: 10.1016/j.esmorw.2025.100495
Authors: C. Trieu, L.T. Arayan, U. Akhouri, E. Vieira, D. Sharma, S. Kalia, T.K.W. Hung, M.E. Delisle, R. Nassar, M. Touma, A. Jaet, S. Alhajsaleh, R. Patel, A. Luginaah, G. Anagnostopoulos, M. Paunic, O. Hilal, M. Hossami, R. Abdel-Nabi, C.M. Hamm
Institutions: University of Windsor, Windsor Regional Hospital, Western University, University of Ottawa, University of Manitoba, University of Toronto
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,170
OpenAlex ID: W4416780896
FWCI:
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