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Exploration of known and unknown early symptoms of cervical cancer and development of a symptom spectrum: Outline of a data and text mining based approach
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2015 (English)In: Proceedings of the CAiSE-2015 Industry Track: co-located with 27th Conference on Advanced Information Systems Engineering (CAiSE 2015) / [ed] John Krogstie, Gustaf Juel-Skielse, Vandana Kabilan, 2015, 34-44 p.Conference paper, Published paper (Refereed)
Abstract [en]

This position paper lays up the structure of some experiments to detect early symptoms of cervical cancer. We are using a large corpora of electronic patient records texts in Swedish from Karolinska University Hosptital from the years 2009-2010, where we extracted in total 1,660 patients with the diagnosis code C53. We used a Named Entity Recogniser called Clinical Entity Finder to detect the diagnosis and symptoms expressed in these clinical texts containing in total 2,988,118 words. We found 28,218 symptoms and diagnoses on these 1,660 patients. We present some initial findings, and discuss them and propose a set of experiments to find possible early symptoms or at least a spectrum or finger prints for early symptoms of cervical cancer.

Place, publisher, year, edition, pages
2015. 34-44 p.
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 1381
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-119908OAI: oai:DiVA.org:su-119908DiVA: diva2:868548
Conference
27th International Conference on Advanced Information Systems Engineering: CAiSE-2015 Industry Track, Stockholm, Sweden, 11 June, 2015
Available from: 2015-11-11 Created: 2015-08-28 Last updated: 2017-02-02Bibliographically approved

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