Literature DB >> 25155030

University of California, Irvine-Pathology Extraction Pipeline: the pathology extraction pipeline for information extraction from pathology reports.

Naveen Ashish1, Lisa Dahm2, Charles Boicey2.   

Abstract

We describe Pathology Extraction Pipeline (PEP)--a new Open Health Natural Language Processing pipeline that we have developed for information extraction from pathology reports, with the goal of populating the extracted data into a research data warehouse. Specifically, we have built upon Medical Knowledge Analysis Tool pipeline (MedKATp), which is an extraction framework focused on pathology reports. Our particular contributions include additional customization and development on MedKATp to extract data elements and relationships from cancer pathology reports in richer detail than at present, an abstraction layer that provides significantly easier configuration of MedKATp for extraction tasks, and a machine-learning-based approach that makes the extraction more resilient to deviations from the common reporting format in a pathology reports corpus. We present experimental results demonstrating the effectiveness of our pipeline for information extraction in a real-world task, demonstrating performance improvement due to our approach for increasing extractor resilience to format deviation, and finally demonstrating the scalability of the pipeline across pathology reports for different cancer types.
© The Author(s) 2014.

Entities:  

Keywords:  Clinical decision-making; databases and data mining; decision-support systems; evidence-based practice; information and knowledge management

Mesh:

Year:  2014        PMID: 25155030     DOI: 10.1177/1460458213494032

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  10 in total

1.  Classification of hepatocellular carcinoma stages from free-text clinical and radiology reports.

Authors:  Wen-Wai Yim; Sharon W Kwan; Guy Johnson; Meliha Yetisgen
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

2.  Parsing clinical text using the state-of-the-art deep learning based parsers: a systematic comparison.

Authors:  Yaoyun Zhang; Firat Tiryaki; Min Jiang; Hua Xu
Journal:  BMC Med Inform Decis Mak       Date:  2019-04-04       Impact factor: 2.796

3.  A Frame-Based NLP System for Cancer-Related Information Extraction.

Authors:  Yuqi Si; Kirk Roberts
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

4.  Automated medical chart review for breast cancer outcomes research: a novel natural language processing extraction system.

Authors:  Yifu Chen; Lucy Hao; Vito Z Zou; Zsuzsanna Hollander; Raymond T Ng; Kathryn V Isaac
Journal:  BMC Med Res Methodol       Date:  2022-05-12       Impact factor: 4.612

Review 5.  Natural language processing systems for capturing and standardizing unstructured clinical information: A systematic review.

Authors:  Kory Kreimeyer; Matthew Foster; Abhishek Pandey; Nina Arya; Gwendolyn Halford; Sandra F Jones; Richard Forshee; Mark Walderhaug; Taxiarchis Botsis
Journal:  J Biomed Inform       Date:  2017-07-17       Impact factor: 6.317

6.  Tumor information extraction in radiology reports for hepatocellular carcinoma patients.

Authors:  Wen-Wai Yim; Tyler Denman; Sharon W Kwan; Meliha Yetisgen
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2016-07-20

7.  Application of Text Information Extraction System for Real-Time Cancer Case Identification in an Integrated Healthcare Organization.

Authors:  Fagen Xie; Janet Lee; Corrine E Munoz-Plaza; Erin E Hahn; Wansu Chen
Journal:  J Pathol Inform       Date:  2017-12-14

8.  Automated extraction of Biomarker information from pathology reports.

Authors:  Jeongeun Lee; Hyun-Je Song; Eunsil Yoon; Seong-Bae Park; Sung-Hye Park; Jeong-Wook Seo; Peom Park; Jinwook Choi
Journal:  BMC Med Inform Decis Mak       Date:  2018-05-21       Impact factor: 2.796

Review 9.  Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review.

Authors:  Seyedmostafa Sheikhalishahi; Riccardo Miotto; Joel T Dudley; Alberto Lavelli; Fabio Rinaldi; Venet Osmani
Journal:  JMIR Med Inform       Date:  2019-04-27

Review 10.  Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing.

Authors:  Liwei Wang; Sunyang Fu; Andrew Wen; Xiaoyang Ruan; Huan He; Sijia Liu; Sungrim Moon; Michelle Mai; Irbaz B Riaz; Nan Wang; Ping Yang; Hua Xu; Jeremy L Warner; Hongfang Liu
Journal:  JCO Clin Cancer Inform       Date:  2022-07
  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.