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Information extraction for prognostic stage prediction from breast cancer medical records using NLP and ML

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Abstract

For cancer prediction, the prognostic stage is the main factor that helps medical experts to decide the optimal treatment for a patient. Specialists study prognostic stage information from medical reports, often in an unstructured form, and take a larger review time. The main objective of this study is to suggest a generic clinical decision-unifying staging method to extract the most reliable prognostic stage information of breast cancer from medical records of various health institutions. Additional prognostic elements should be extracted from medical reports to identify the cancer stage for getting an exact measure of cancer and improving care quality. This study has collected 465 pathological and clinical reports of breast cancer sufferers from India’s reputed medical institutions. The unstructured records were found distinct from each institute. Anatomic and biologic factors are extracted from medical records using the natural language processing, machine learning and rule-based method for prognostic stage detection. This study has extracted anatomic stage, grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) from medical reports with high accuracy and predicted prognostic stage for both regions. The prognostic stage prediction’s average accuracy is found 92% and 82% in rural and urban areas, respectively. It was essential to combine biological and anatomical elements under a single prognostic staging method. A generic clinical decision-unifying staging method for prognostic stage detection with great accuracy in various institutions of different regional areas suggests that the proposed research improves the prognosis of breast cancer.

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Acknowledgements

The authors would like to convey thanks to Nurgis Dutta Memorial Cancer Hospital (NDMCH) in the rural region and Jehangir Hospital (JH) and different laboratories in the urban area for allowing access to their medical records. The authors also want to acknowledge Ethics Committees for approving proposed research. The authors would like to express their gratitude to Dr. Nene, Dr. Chauhan, Dr. Joshi, Dr. Shilpa, Dr. Vibhute, and Dr. Mane for their guidance in the medical field. Thanks to all patients with breast cancer for letting the authors use their medical records for this research. The authors would like to thank Harshal Ingale for his cooperation.

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  1. School of Computer Engineering and Technology, MIT World Peace University, Pune, India, 411029

    Pratiksha R. Deshmukh & Rashmi Phalnikar

  2. Department of Computer Engineering and Information Technology, College of Engineering, Pune, 411005, India

    Pratiksha R. Deshmukh

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  1. Pratiksha R. Deshmukh
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Correspondence to Pratiksha R. Deshmukh.

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Deshmukh, P.R., Phalnikar, R. Information extraction for prognostic stage prediction from breast cancer medical records using NLP and ML. Med Biol Eng Comput 59, 1751–1772 (2021). https://doi.org/10.1007/s11517-021-02399-7

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