{
    "ok": true,
    "doi": "10.46243/jst.2023.v8.i07.pp45-57",
    "doi_display": "10.46243/jst.2023.v8.i07.pp45-57",
    "doi_url": "https://doi.org/10.46243/jst.2023.v8.i07.pp45-57",
    "state": "registered",
    "url": "https://www.jst.org.in/index.php/pub/article/view/697",
    "title": "IDENTIFYING HEALTH INSURANCE CLAIM FRAUDS USING MACHINE LEARNING CONCEP",
    "version": 2,
    "registered_via": "crossref",
    "prefix": {
        "prefix": "10.46243",
        "status": "live"
    },
    "registrant": {
        "name": "Longman Publishers",
        "kind": "publisher",
        "country": "India"
    },
    "reserved_at": null,
    "registered_at": "2026-09-29 22:00:28",
    "updated_at": "2026-09-29 23:59:47",
    "withdrawn_at": null,
    "withdrawn_reason": null,
    "record": {
        "format": "smartscholars-doi-metadata/1.0",
        "doi": "10.46243/jst.2023.v8.i07.pp45-57",
        "referent": "Creation",
        "type": "JournalArticle",
        "structural_type": "Digital",
        "modes": [
            "Visual"
        ],
        "characters": [
            "Language"
        ],
        "titles": [
            {
                "value": "IDENTIFYING HEALTH INSURANCE CLAIM FRAUDS USING MACHINE LEARNING CONCEP",
                "type": "PrincipalTitle",
                "lang": "en"
            }
        ],
        "identifiers": [
            {
                "type": "DOI",
                "value": "10.46243/jst.2023.v8.i07.pp45-57"
            }
        ],
        "agents": [
            {
                "role": "author",
                "name": {
                    "given": "Mrs. K. Aarati",
                    "family": "Mrs. K. Aarati"
                },
                "sequence": "first"
            },
            {
                "role": "publisher",
                "name": {
                    "org": "Longman Publishers"
                }
            }
        ],
        "dates": {
            "published": "2023-08-07",
            "date_type": "PublicationDate",
            "online": "2023-08-07"
        },
        "language": "en",
        "container": {
            "type": "Journal",
            "titles": [
                {
                    "value": "Journal of Science & Technology",
                    "type": "PrincipalTitle"
                }
            ],
            "identifiers": [
                {
                    "type": "ISSN",
                    "value": "2456-5660",
                    "medium": "electronic"
                }
            ],
            "volume": "8",
            "issue": "7",
            "pages": {
                "first": "45",
                "last": "57"
            }
        },
        "links": [
            {
                "url": "https://www.jst.org.in/index.php/pub/article/view/697",
                "return_type": "text/html",
                "primary": true
            },
            {
                "url": "https://www.jst.org.in/index.php/pub/article/download/697/628",
                "purpose": "text-mining",
                "return_type": "application/pdf"
            },
            {
                "url": "https://www.jst.org.in/index.php/pub/article/download/697/1724",
                "purpose": "text-mining",
                "return_type": "application/xml"
            }
        ],
        "abstract": {
            "value": "Patients depend on health insurance provided by the governmentsystems, private systems, or both to utilizethe high-priced healthcare expenses. Thisdependency on health insurance draws some healthcare service providers to commit insurance frauds. In this paper, we perform a comparative analysis on various classification algorithms, namely Support Vector Machine (SVM), Decision-Tree (DT), K-Nearest Neighbor (KNN), Logistic Regression (LR), to detect the health insurance fraud. The effectiveness of the algorithms are observed on the basis of performance metrics: Precision, Recall and F1-Score",
            "lang": "en"
        },
        "license": {
            "url": "https://creativecommons.org/licenses/by/4.0",
            "start": "2023-08-07",
            "applies_to": "vor"
        },
        "record": {
            "registrant": "Longman Publishers",
            "registered": "2024-02-16",
            "updated": "2026-09-28",
            "issue_number": 1,
            "source": "crossref-api",
            "source_agency": "Crossref (member 25296)"
        }
    },
    "record_sha256": "e3b1a78f4c785de6a8f1c4890e11792e8c0218cbaf5da047f4c3c6249e02cc73",
    "handle": {
        "synced_at": "2026-10-01 18:12:48",
        "url": "https://www.jst.org.in/index.php/pub/article/view/697"
    },
    "links": {
        "record_page": "https://registry.smartscholars.in/record.php?doi=10.46243%2Fjst.2023.v8.i07.pp45-57",
        "system_metadata": "https://registry.smartscholars.in/resolve.php?doi=10.46243%2Fjst.2023.v8.i07.pp45-57&as=system",
        "history": "https://registry.smartscholars.in/api.php?action=history&doi=10.46243%2Fjst.2023.v8.i07.pp45-57",
        "kernel_xml": "https://registry.smartscholars.in/resolve.php?doi=10.46243%2Fjst.2023.v8.i07.pp45-57&as=xml"
    }
}