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Prognostic elements extraction from documents to detect prognostic stage

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  • Pratiksha R. Deshmukh
  • Rashmi Phalnikar

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.

Suggested Citation

  • Pratiksha R. Deshmukh & Rashmi Phalnikar, 2022. "Prognostic elements extraction from documents to detect prognostic stage," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 25(4), pages 371-386, March.
    • Handle: RePEc:taf:gcmbxx:v:25:y:2022:i:4:p:371-386
    DOI: 10.1080/10255842.2021.1955359
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