10.46243/jst.2023.v8.i06.pp45-57 registered
IDENTIFYING HEALTH INSURANCE CLAIM FRAUDS USING MACHINE LEARNING CONCEPT
Resolves to https://www.jst.org.in/index.php/pub/article/view/697
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2023.v8.i06.pp45-57
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 7887f8355a5352c0…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
IDENTIFYING HEALTH INSURANCE CLAIM FRAUDS USING MACHINE LEARNING CONCEPT (PrincipalTitle)
Published 2022-05-11
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 7 · issue 9 · pages 45–57
Agents
- Mrs. K. Aarati Mrs. K. Aarati (author)
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2023.v8.i06.pp45-57
Abstract
Patients depend on health insurance provided by the governmentsystems, private systems, or both to utilizethe high-priced healthcare expenses. This dependency 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
System metadata — ISO 26324:2025, Annex B · DOI Handbook 10.1
Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2023.v8.i06.pp45-57 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | IDENTIFYING HEALTH INSURANCE CLAIM FRAUDS USING MACHINE LEARNING CONCEPT (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Mrs. K. Aarati Mrs. K. Aarati publisher: Longman Publishers published: 2022-05-11 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 9 · pp. 45–57 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2024-02-16 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
The System Metadata Declaration (JSON) · the Kernel Metadata Declaration (XML) · what each sub-type needs
History — the ledger
Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 63 fields set · sha256 c8dfb2618fab… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | agents.0.name.family: agents.0.name.given: container.titles.0.value: |
Machine-readable: the history as JSON, with the full record after each change.
