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Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

Cancers(2023)10.3390/cancers15174372Source: DataRank Database

Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors is a research paper published in Cancers (2023). On theSindex it has a DataRank of 0.789. It has been cited 15 times, with 12 citing works in its 1-hop citation network.

N/A

0.789DataRank · unranked

Scored on demand from live citation data

Open Access15 citations · 12 citing works in its network

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 3.80)OA: goldTopics (19)IDs (PubMed, PMC, OpenAlex)SDGs (1)

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 53%Citation Network 47%

Base Score Contribution

0.416

From this paper's citation signal

Citation Network Contribution

0.373

From 10 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 12 citers.

A CT-based deep learning model predicts overall survival in patients with muscle invasive bladder cancer after radical cystectomy: a multicenter retrospective cohort study
International Journal of Surgery202435 citations42 referencesContributes 0.085
Coupling Habitat Radiomic Analysis with the Diversification of the Tumor ecosystem: Illuminating New Strategy in the Assessment of Postoperative Recurrence of Non-Muscle Invasive Bladder Cancer
Academic Radiology202414 citations32 referencesContributes 0.085
Survival After Radical Cystectomy for Bladder Cancer: Development of a Fair Machine Learning Model
JMIR Medical Informatics20243 citations27 referencesContributes 0.051
An interpretable CT-based deep learning model for predicting overall survival in patients with bladder cancer: a multicenter study
npj Precision Oncology20256 citations41 referencesContributes 0.047
Accurate bladder cancer diagnosis using ensemble deep leaning
Scientific Reports20256 citations53 referencesContributes 0.037

Authors (9)

Lubomir M. Hadjiiski ORCID,John Gormley ORCID,Heang‐Ping Chan ORCID,Elaine M. Caoili ORCID,Richard H. Cohan ORCID

Live enrichment

PubMed:37686647 PMC:PMC10486459 OpenAlex:https://openalex.org/W4386377962

National Institutes of Health

Grant: U01-CA232931

NCI NIH HHS

Grant: U01 CA232931

National Institutes of Health

Grant: 5U01CA232931-04

Biomarker-Based Tools for Treatment Response Decision Support of Bladder Cancer

FWCI

3.80

Citation Percentile

0.9%

Citation Trend

2024

2025

goldLicense: cc-by

journalhttps://www.mdpi.com/2072-6694/15/17/4372/pdf?version=1693556143

publisherhttps://www.mdpi.com/2072-6694/15/17/4372/pdf?version=1693556143

publisherhttps://www.mdpi.com/2072-6694/15/17/4372/pdf

journalhttps://doi.org/10.3390/cancers15174372

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37686647

Fields of Study

Bladder and Urothelial Cancer TreatmentsColorectal Cancer Screening and DetectionRadiomics and Machine Learning in Medical Imaging03 medical and health sciences0302 clinical medicine

Keywords

RadiomicsCystectomyBladder cancerMedicineCancerArtificial intelligenceInternal medicineRadiologyComputer scienceRadical CystectomyNomogramSurvival PredictionDeep LearningArticle

Sustainable Development Goals

SDG 0: Good health and well-being