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10.46243/jst.2022.v7.i01.pp188-198 registered

EFFICIENT MACHINE LEARNING MODEL TO IDENTIFY THE LUNG CANCER USING DYNAMIC FEATURE EXTARCTION

Resolves to https://www.jst.org.in/index.php/pub/article/view/349

Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2022.v7.i01.pp188-198

Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 0f855994813d31ae…

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What the DOI identifies

JournalArticle — an article in a journal · Digital · Visual · en

EFFICIENT MACHINE LEARNING MODEL TO IDENTIFY THE LUNG CANCER USING DYNAMIC FEATURE EXTARCTION (PrincipalTitle)

Published 2023-07-26

Part of Journal of Science & Technology · ISSN 2456-5660 · volume 7 · issue 1 · pages 188–198

Agents

  • ASIYA ASIYA (author)
  • Longman Publishers (publisher)

Identifiers DOI 10.46243/jst.2022.v7.i01.pp188-198

Abstract

An estimated 1.2 million people were diagnosed with lung cancer in 2000, making it the most frequent disease worldwide (12.3% of all malignancies). Cigarette smokers are responsible for 80% to 90% of lung cancers. In both sexes, lung cancer continues to be the major cause of cancer-related death in the United States and elsewhere. Tobacco use and smoking are responsible for nearly all occurrences of lung cancer. Other causes of lung cancer include exposure to radon gas, asbestos, air pollution, and persistent infections. Further, many potential risk factors for developing lung cancer have been proposed, including both genetic and environmental factors. Small-cell lung carcinomas (SCLC) and non-small-cell lung carcinomas (NSCLC) are the two main histologic subtypes of lung cancer and exhibit distinct patterns of growth and metastasis (NSCLC). Surgery, radiation treatment, chemotherapy, and targeted therapy are all viable alternatives for treating lung cancer. Different characteristics, such as the nature and extent of the malignancy, inform suggestions for treatment approaches. A diagnosis of lung cancer at an early stage can save the lives of patients. Several machine learning algorithms were used to make lung cancer forecasts in this study.

Licence https://creativecommons.org/licenses/by/4.0

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.

ElementValueIn the record
DOI Name
DOI name
10.46243/jst.2022.v7.i01.pp188-198doi
Referent Type
referentType
Creationreferent
Referent Sub-Type
referentSubType
JournalArticle — an article in a journaltype
Referent Name(s)
referentName(s)
EFFICIENT MACHINE LEARNING MODEL TO IDENTIFY THE LUNG CANCER USING DYNAMIC FEATURE EXTARCTION (PrincipalTitle, en)titles
Basic Metadata
basicMetadata
author: ASIYA ASIYA
publisher: Longman Publishers
published: 2023-07-26
part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 7 · no. 1 · pp. 188–198
language: en
form: Digital · Visual · Language
agents, dates, container, language, structural_type, modes, characters
Referent Identifier(s)
alternateIdentifier(s)
none besides the DOIidentifiers, relations (IsSameAs)
Registration Authority
registrationAuthorityCode
Crossref — issued by Crossref (member 25296); held here as a copyrecord.source_agency (our code, ra_doi_name, for names issued here once appointed)
Created Date
issueDate
2024-02-16record.registered (when the DOI name was first registered)
relatedIdentifiersnone needed — the descriptive metadata is in this recordcontainer, 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.

Recommended for a journal article and not in this record: the reference list.

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.

#WhenWhatByChanges
129 Sep 2026, 10:00 PMregister
registered at Crossref; record read from api.crossref.org
Administrator (admin) 52 fields set · sha256 4d77af6b4d9e…
229 Sep 2026, 11:59 PMupdate
record re-read from api.crossref.org
Administrator (admin)
container.titles.0.value: Journal of Science & Technology → Journal of Science & Technology

Machine-readable: the history as JSON, with the full record after each change.

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