International Journal of Research in Signal Processing, Computing & Communication System Design

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Review on Health Care Claim Processing Using Text Mining and Natural Language Processing


Affiliations
1 Birla Vishvakarma Mahavidyalaya Engineering College, Vidyanagar, Anand, Gujarat, India
     

   Subscribe/Renew Journal


The processing of health care claims includes a combination of structured and unstructured data collected from various sources of information that are directly or indirectly related to the medical insurance claim. Such processing takes help of Natural Language processing along with some concept specific language. NLP Techniques along with Text Mining helps in finding dependencies between different entities which further generate scores for individual claims. These scores are considered in making decisions involving determination of fraud or genuine claims by the client.

Keywords

Categorization, Information Retrieval, Medical Claims, Natural Language Processing (NLP), Pattern Matching, Text Mining.
User
Subscription Login to verify subscription
Notifications
Font Size

  • D. Jurafsky, J. Martin, Speech and Language Processing, Prentice Hall, Upper Sale River, NJ, 2000.

  • D. Mladenic, and M. Grobelnik, “Text and Web Mining,” in D. Mladenic, N. Lavrac, M. Bohanec, and S. Moyle, (eds.), Data Mining and Decision Support Integration and Collaboration, Kluwer, Dordrecht, 2003.

  • F. Popowich, “Using text mining and natural language processing for health care claims processing,” SIGKDD Explorations, vol. 7, no. 1, pp. 59-66, ACM, June 2005. Available: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.97.5598&rep=rep1&type=pdf

  • RecordOne, “Is natural language processing the key to data-driven health care?,” 2015. Available: http://www.recordsone.com/wp-content/uploads/2015/05/R1_NLP_WP_web.pdf

  • F. Popowich, “Use of text analytics and taxonomies for fraud and abuse detection in medical insurance claims,” Proceedings of Semantic Web Symposium of I2LOR-04 Towards the Educational Semantic Web (Université de Quebec à Montréal, Montréal), 19 November 2004. Available: http://www.cscsi.org/home/CSCSI/Members/swig/swig04papers/popowich-swig.pdf

  • S. Abney, “Part-of-speech tagging and partial parsing,” in S. Young, and G. Bloothooft, (eds.), Corpus-Based Methods in Language and Speech Processing, Kluwer, Dordrecht, pp. 118-136, 1997. J. Han, and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, San Francisco, CA, 2000.


Abstract Views: 161

PDF Views: 0




  • Review on Health Care Claim Processing Using Text Mining and Natural Language Processing

Abstract Views: 161  |  PDF Views: 0

Authors

Tushar Gonawala
Birla Vishvakarma Mahavidyalaya Engineering College, Vidyanagar, Anand, Gujarat, India
Hima Khimani
Birla Vishvakarma Mahavidyalaya Engineering College, Vidyanagar, Anand, Gujarat, India
Ruchi Patel
Birla Vishvakarma Mahavidyalaya Engineering College, Vidyanagar, Anand, Gujarat, India
Vatsal Shah
Birla Vishvakarma Mahavidyalaya Engineering College, Vidyanagar, Anand, Gujarat, India

Abstract


The processing of health care claims includes a combination of structured and unstructured data collected from various sources of information that are directly or indirectly related to the medical insurance claim. Such processing takes help of Natural Language processing along with some concept specific language. NLP Techniques along with Text Mining helps in finding dependencies between different entities which further generate scores for individual claims. These scores are considered in making decisions involving determination of fraud or genuine claims by the client.

Keywords


Categorization, Information Retrieval, Medical Claims, Natural Language Processing (NLP), Pattern Matching, Text Mining.

References