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A Systematic Review on Application of Multimodal Learning and Explainable AI in Tuberculosis Detection

IEEE Access(2025)10.1109/access.2025.3558878Source: DataRank Database

A Systematic Review on Application of Multimodal Learning and Explainable AI in Tuberculosis Detection is a research paper published in IEEE Access (2025). On theSindex it has a DataRank of 0.416. It has been cited 15 times.

N/A

0.416DataRank · unranked

Scored on demand from live citation data

Open Access15 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (2 grants)Impact (FWCI 5.04)OA: goldTopics (15)IDs (PubMed, OpenAlex)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.416

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

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Authors (4)

Joyce Nakatumba‐Nabende ORCID,Andrew Katumba ORCID,David Patrick Kateete ORCID,Barbara Nansamba ORCID

Live enrichment

PubMed:19767382 OpenAlex:https://openalex.org/W4409249102

Fogarty International Center of the National Institutes of Health

Grant: U2RTW012116

National Institutes of Health

Grant: 5U2RTW012116-05

Makerere University Data Science Research Training to Strengthen Evidence-Based Health Innovation, Intervention and Policy (MakDARTA)

FWCI

5.04

Citation Percentile

1.0%

Citation Trend

2025

2026

goldLicense: cc-by

journalhttps://doi.org/10.1109/access.2025.3558878

publisherhttps://doi.org/10.1109/access.2025.3558878

publisherhttp://xplorestaging.ieee.org/ielx8/6287639/10820123/10955390.pdf?arnumber=10955390

repositoryhttps://doaj.org/article/0bd92662fbe145069132d16a17c31652

https://doi.org/10.1109/ACCESS.2025.3558878

Fields of Study

COVID-19 diagnosis using AIIdeological and Political Education0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Computer scienceArtificial intelligenceTuberculosisMachine learningMedicinemultimodal learningtuberculosis detectionDeep learningElectrical engineering. Electronics. Nuclear engineeringexplainable AITK1-9971