International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Enriching Fraud Claims Detection in Health Sector using Machine Learning Rutuja Dhumal, Harsha Baviskar, Sayali Bhawalkar, Jui Yadav, Prof.Geetanjali Yadav Dept. of Computer, Keystone School of Engineering, Pune, Maharashtra, India DOI: 10.15680/IJIRCCE.2022.1004026 |
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| pdf/SQ8hKL0CcEfsfZJfYxfSJH5LwbpgcHZY9Lb304cA.pdf |
