Prognostic elements extraction from documents to detect prognostic stage

Pratiksha R. Deshmukh and Rashmi Phalnikar

Computer Methods in Biomechanics and Biomedical Engineering, 2022, vol. 25, issue 4, 371-386

Abstract: For cancer prediction, the prognostic stage is the main factor that helps medical experts to decide the optimal treatment for a patient. The main objective of this study is to predict prognostic stage from the medical records of various health institutions. Total 465 pathological and clinical reports of people living with breast cancer has been collected from India's reputed treatment institutions. Different anatomic and biologic factors are extracted from unstructured medical records using a novel combination of natural language processing (NLP) and fuzzy decision tree (FDT) for prognostic stage detection. This study has extracted the anatomic and biologic factors from medical reports with high accuracy. The average accuracy of the prognostic stage prediction found 93% and 83% in rural and urban regions, respectively. A generalized method for cancer staging with great accuracy in a different medical institution from dissimilar regional areas suggest that the proposed research improves the prognosis of breast cancer.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255842.2021.1955359 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:25:y:2022:i:4:p:371-386

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255842.2021.1955359

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().