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∗
2015 (English)Report (Other academic)
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
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-119908OAI: oai:DiVA.org:su-119908DiVA: diva2:868548