Application and validation of AI-driven methods to explore patient experiences of pre-cervical cancer.

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Bibliographic Details
Title: Application and validation of AI-driven methods to explore patient experiences of pre-cervical cancer.
Authors: Luo MY; School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom. Electronic address: myl41@cam.ac.uk., Williams CYK; Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, the United States of America.
Source: European journal of obstetrics, gynecology, and reproductive biology [Eur J Obstet Gynecol Reprod Biol] 2026 Feb 20; Vol. 318, pp. 114953. Date of Electronic Publication: 2026 Jan 10.
Publication Type: Journal Article; Validation Study
Journal Info: Publisher: Elsevier Scientific Publishers Country of Publication: Ireland NLM ID: 0375672 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7654 (Electronic) Linking ISSN: 03012115 NLM ISO Abbreviation: Eur J Obstet Gynecol Reprod Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1872-7654
DOI:10.1016/j.ejogrb.2026.114953