{"doi":"10.1371/journal.pone.0253829","title":"Harnessing clinical annotations to improve deep learning performance in prostate segmentation","abstract":"PURPOSE: Developing large-scale datasets with research-quality annotations is challenging due to the high cost of refining clinically generated markup into high precision annotations. We evaluated the direct use of a large dataset with only clinically generated annotations in development of high-performance segmentation models for small research-quality challenge datasets. MATERIALS AND METHODS: We used a large retrospective dataset from our institution comprised of 1,620 clinically generated segmentations, and two challenge datasets (PROMISE12: 50 patients, ProstateX-2: 99 patients). We trained a 3D U-Net convolutional neural network (CNN) segmentation model using our entire dataset, and used that model as a template to train models on the challenge datasets. We also trained versions of the template model using ablated proportions of our dataset, and evaluated the relative benefit of those templates for the final models. Finally, we trained a version of the template model using an out-of-domain brain cancer dataset, and evaluated the relevant benefit of that template for the final models. We used five-fold cross-validation (CV) for all training and evaluation across our entire dataset. RESULTS: Our model achieves state-of-the-art performance on our large dataset (mean overall Dice 0.916, average Hausdorff distance 0.135 across CV folds). Using this model as a pre-trained template for refining on two external datasets significantly enhanced performance (30% and 49% enhancement in Dice scores respectively). Mean overall Dice and mean average Hausdorff distance were 0.912 and 0.15 for the ProstateX-2 dataset, and 0.852 and 0.581 for the PROMISE12 dataset. Using even small quantities of data to train the template enhanced performance, with significant improvements using 5% or more of the data. CONCLUSION: We trained a state-of-the-art model using unrefined clinical prostate annotations and found that its use as a template model significantly improved performance in other prostate segmentation tasks, even when trained with only 5% of the original dataset.","journal":"PLoS ONE","year":2021,"id":198486,"datarank":0.538510441439189,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.17882615051943335,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.17882615051943335,"corpus_percentile":63.89726928134911,"corpus_rank":4668,"citation_count":10,"citer_count":8,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.8394,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":58.3333,"fair_percentile":72.8829104249465,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":774339,"name":"Alex G. Raman","orcid":null,"position":1,"is_corresponding":false},{"id":517575,"name":"Nikhil J. Dhinagar","orcid":"0000-0003-2424-4854","position":2,"is_corresponding":false},{"id":241707,"name":"Alan Priester","orcid":"0000-0001-9188-5905","position":3,"is_corresponding":false},{"id":110303,"name":"Stephanie A. Harmon","orcid":"0000-0002-2507-2399","position":4,"is_corresponding":false},{"id":453611,"name":"Thomas Sanford","orcid":"0000-0002-7123-9807","position":5,"is_corresponding":false},{"id":218396,"name":"Sherif Mehralivand","orcid":"0000-0003-1405-3683","position":6,"is_corresponding":false},{"id":110339,"name":"Barış Türkbey","orcid":"0000-0003-0853-6494","position":7,"is_corresponding":false},{"id":241708,"name":"Leonard S. Marks","orcid":"0000-0002-7910-179X","position":8,"is_corresponding":false},{"id":241709,"name":"Steven S. Raman","orcid":"0000-0003-0499-1676","position":9,"is_corresponding":false},{"id":241711,"name":"William Speier","orcid":"0000-0002-0890-8684","position":10,"is_corresponding":false},{"id":241712,"name":"Corey Arnold","orcid":"0000-0002-4119-8143","position":11,"is_corresponding":false},{"id":6236,"name":"Karthik V. Sarma","orcid":"0000-0002-7442-9526","position":0,"is_corresponding":true}],"reference_count":27,"raw_metadata":null,"created_at":"2026-07-18T23:50:31.857233Z","pmid":"34170972","pmcid":"PMC8232529","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":83.3333,"fair_a":62.5,"fair_i":20.0,"fair_r":25.0,"fair_zscore":0.9454,"fair_rationale":{"fair_score":58.33,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":83.33,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"10.5068/D1J09F","grounded":true,"rationale":"The paper provides a DOI (10.5068/D1J09F) for the deposited summary statistics, which is a persistent identifier scheme.","anchors":["RDA-F1-01D — FAIR Data Maturity Model: 'Data is identified by a persistent identifier' (priorit","RDA-F1-02D — FAIR Data Maturity Model: 'Data is identified by a globally unique identifier'","FsF-F1-02D — F-UJI/FAIRsFAIR: 'Data is assigned a persistent identifier'"],"scored":true,"signal":null},{"key":"f_repository_named","label":"Named repository","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"Dryad repository","grounded":true,"rationale":"The paper names the Dryad repository as the holder of the deposited data.","anchors":["RDA-F4-01M — FAIR Data Maturity Model: metadata is offered so it can be harvested and indexed (","NIH DMS Policy Element 4 (NOT-OD-21-014) — name the repository where data will be archived","NSTC Desirable Characteristics of Data Repositories (2022) — 'Long-Term Sustainability', 'Reten"],"scored":true,"signal":null},{"key":"f_data_availability_statement","label":"Data-availability statement","kind":"llm","weight":2.0,"fraction":1.0,"verdict":"yes","evidence":"The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F","grounded":true,"rationale":"The data availability statement points to a repository record (Dryad with DOI), which is a persistent repository link (Colavizza category 3). 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[majority verdict 'partial' (3/5 passes agreed)]","anchors":["FsF-A1-01M — F-UJI: 'Metadata contains access level and access conditions of the data'","RDA-A1-01M — metadata contains information to enable the user to get access to the data","COAR Controlled Vocabularies — Access Rights v1.0 (open / embargoed / restricted / metadata-onl"],"scored":false,"signal":null},{"key":"a_controlled_access_for_sensitive","label":"Gatekeeper for sensitive data","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper states that the clinical imaging data cannot be shared publicly due to privacy, but does not name any gatekeeper or access route for that data.","anchors":["NIH Genomic Data Sharing Policy (NOT-OD-14-124) — controlled-access via a Data Access Committee","RDA-A1.2-01D — 'Data is accessible through an access protocol that supports authentication and ","NIH DMS Policy Element 5 (NOT-OD-21-014) — Access, Distribution, or Reuse Considerations (conse"],"scored":false,"signal":null},{"key":"a_timeline_retention","label":"Availability timing & retention","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not mention any retention period, permanence, or timing of availability for the deposited data. [majority verdict 'no' (4/5 passes agreed)]","anchors":["NIH DMS Plan Element 4 (NOT-OD-21-014) — Data Preservation, Access, and Associated Timelines","NSTC Desirable Characteristics (2022), Organizational Infrastructure: 'Retention Policy'","RDA-A2-01M — 'Metadata is guaranteed to remain available after data is no longer available'"],"scored":false,"signal":null}]},"I":{"name":"Interoperable","score":20.0,"criteria":[{"key":"i_open_nonproprietary_format","label":"Open file format","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not specify any file format for the deposited data.","anchors":["FsF-R1.3-02D — F-UJI: 'Data is available in a file format recommended by the target research co","RDA-R1.3-02D — data is expressed in a machine-understandable community standard","RDA-I1-01D — data uses a knowledge representation expressed in a standardised format"],"scored":true,"signal":null},{"key":"i_community_standard_vocabulary","label":"Community standard / vocabulary","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No data or metadata community standard (e.g., MIAME, BIDS, GO) is named in the paper.","anchors":["RDA-R1.3-01M — 'Metadata complies with a community standard' (priority Essential)","RDA-R1.3-01D — 'Data complies with a community standard'","RDA-I2-01M — '(Meta)data use vocabularies that follow FAIR principles'"],"scored":false,"signal":null},{"key":"i_qualified_references","label":"Identifiers for the resources the data depend on","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"The PROMISE12 grand challenge dataset is made available by its owners here: https://promise12.grand-challenge.org/","grounded":true,"rationale":"The paper provides a repository URL for the PROMISE12 dataset, which is a qualified reference to an external resource. [majority verdict 'yes' (3/5 passes agreed)]","anchors":["RDA-I3-01M — '(meta)data include references to other (meta)data'","RDA-I3-03M — 'metadata includes qualified references to other metadata'","FsF-I3-01M — F-UJI: 'Metadata includes links between the data and its related entities'"],"scored":false,"signal":null}]},"R":{"name":"Reusable","score":25.0,"criteria":[{"key":"r_reuse_license","label":"Reuse licence","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No license is stated for the deposited data; the CC0 license applies to the article, not the data.","anchors":["RDA-R1.1-01M — 'Metadata includes information about the licence under which the data can be reu","RDA-R1.1-02M — 'Metadata refers to a standard reuse licence'","RDA-R1.1-03M — 'Metadata refers to a machine-understandable reuse licence'"],"scored":true,"signal":null},{"key":"r_provenance_methods","label":"Provenance of the data","kind":"llm","weight":1.0,"fraction":1.0,"verdict":"yes","evidence":"3T magnet (Trio, Verio, or Skyra, Siemens Healthcare)","grounded":true,"rationale":"The paper names specific instruments, platforms, and software used to generate the data.","anchors":["RDA-R1.2-01M — 'Metadata includes provenance information according to community- specific standa","FsF-R1.2-01M — F-UJI: 'Metadata includes provenance information about data creation or generati","W3C PROV-O (W3C Recommendation, 2013) — the entity/activity/agent model of provenance"],"scored":false,"signal":null},{"key":"r_documentation_codebook","label":"Documentation / codebook","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No README, data dictionary, or codebook is mentioned as accompanying the deposited data.","anchors":["RDA-R1-01M — '(Meta)data are richly described with a plurality of accurate and relevant attribu","FsF-R1-01MD — F-UJI: 'Metadata specifies the content of the data'","NIH DMS Policy Element 3 (NOT-OD-21-014) — Standards (documentation and metadata to accompany t"],"scored":false,"signal":null},{"key":"r_versioning","label":"Snapshot identified","kind":"llm","weight":0.5,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"No version token or date is provided for the deposited data snapshot.","anchors":["DataCite Metadata Schema 4.6 — the 'Version' property","RDA-R1.2-01M — provenance information (which version was used is provenance)","NSTC Desirable Characteristics of Data Repositories (2022) — 'Provenance', 'Retention Policy'"],"scored":true,"signal":null},{"key":"x_code_availability","label":"Analysis code available","kind":"llm","weight":1.0,"fraction":0.0,"verdict":"no","evidence":null,"grounded":false,"rationale":"The paper does not provide any locator for the study's own code; only third-party tools are named.","anchors":["NIH DMS Policy Element 2 (NOT-OD-21-014) — 'Related Tools, Software and/or Code'","FAIR4RS Principles v1.0 (Chue Hong et al., 2022; RDA/FORCE11/ReSA) — FAIR Principles for Resear","FORCE11 Software Citation Principles (Smith, Katz & Niemeyer, 2016, PeerJ CS 2:e86)"],"scored":true,"signal":null},{"key":"x_funding_attribution","label":"Funder and award number","kind":"llm","weight":0.5,"fraction":1.0,"verdict":"yes","evidence":"National Cancer Institute grant F30CA210329","grounded":true,"rationale":"The paper lists specific grant numbers from named funders.","anchors":["DataCite Metadata Schema 4.6 — 'FundingReference' property (funderName, funderIdentifier, award","Crossref Funder Registry — canonical funder identifiers for funding metadata","RDA-F2-01M — rich metadata provided to allow discovery (funding is part of the descriptive reco"],"scored":true,"signal":null}]}},"actions":[{"key":"r_reuse_license","dimension":"R","label":"Reuse licence","action":"Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No license is stated for the deposited data; the CC0 license applies to the article, not the data.","gain":16.67,"priority":"essential","scored":true},{"key":"i_open_nonproprietary_format","dimension":"I","label":"Open file format","action":"Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not specify any file format for the deposited data.","gain":8.33,"priority":"important","scored":true},{"key":"x_code_availability","dimension":"R","label":"Analysis code available","action":"Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not provide any locator for the study's own code; only third-party tools are named.","gain":8.33,"priority":"important","scored":true},{"key":"f_dataset_cited","dimension":"F","label":"Dataset formally cited","action":"Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F","why":"The dataset identifier appears only in the body text of the data availability statement, not in the reference list. [majority verdict 'partial' (3/5 passes agreed)]","gain":4.17,"priority":"important","scored":true},{"key":"r_versioning","dimension":"R","label":"Snapshot identified","action":"Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No version token or date is provided for the deposited data snapshot.","gain":4.17,"priority":"useful","scored":true},{"key":"f_discovery_metadata","dimension":"F","label":"Description of the dataset as an object","action":"Add a 'Data Records' section: itemise every file in the deposit and every variable or sample it holds, with counts and units. Describe the dataset as an object in its own right, not as a by-product of the findings — this is what makes it discoverable to someone who is not looking for your paper.","anchors":["yes","partial","no"],"verdict":"partial","current":0.5,"evidence":"The values behind the means, standard deviations and statistical tests reported are available on the Dryad repository with the DOI 10.5068/D1J09F","why":"The dataset content is described in a single sentence rather than an itemised inventory, section, or table. [majority verdict 'partial' (3/5 passes agreed)]","gain":0.0,"priority":"essential","scored":false},{"key":"a_access_conditions_stated","dimension":"A","label":"Access level labelled","action":"State the access level in words, using the standard vocabulary: 'These data are open access' / 'These data are controlled access'. 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A reporting checklist standardises your paper; it does nothing for your data. In clinical / human-subjects, describe the data with OMOP CDM, CDISC SDTM or HL7 FHIR.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"No data or metadata community standard (e.g., MIAME, BIDS, GO) is named in the paper.","gain":0.0,"priority":"important","scored":false},{"key":"r_documentation_codebook","dimension":"R","label":"Documentation / codebook","action":"Ship a README and a data dictionary IN the deposit — every file, every variable, its units, its allowed values, its missing-value codes. 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For sensitive/human clinical / human-subjects data, use a controlled-access repository such as dbGaP or EGA.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper states that the clinical imaging data cannot be shared publicly due to privacy, but does not name any gatekeeper or access route for that data.","gain":0.0,"priority":"useful","scored":false},{"key":"a_timeline_retention","dimension":"A","label":"Availability timing & retention","action":"State when the data become available AND how long they will be retained — cite the repository's preservation policy. NIH DMS Element 4 asks for both; most papers give neither.","anchors":["yes","partial","no"],"verdict":"no","current":0.0,"evidence":null,"why":"The paper does not mention any retention period, permanence, or timing of availability for the deposited data. [majority verdict 'no' (4/5 passes agreed)]","gain":0.0,"priority":"useful","scored":false}],"suggestions":["Attach a standard, machine-readable open licence to the deposit — CC0 or CC BY, which is what Horizon Europe and most funders expect — and print the licence identifier in the paper. 'Free to use' is not a licence: it grants nothing a reuser's institution can rely on.","Release the data in an open, community-standard format (CSV/TSV, JSON, HDF5, NetCDF, FASTQ, VCF, NIfTI…) instead of — or alongside — any proprietary or instrument-native format, and name the format in the paper. A dataset that needs a €2,000 licence to open is not reusable.","Publish the analysis code in a public forge, archive a tagged release with a DOI (Zenodo/Software Heritage), and cite that DOI in the paper. NIH DMS Element 2 asks for the tools and code, not only the data — and 'available on request' is not a locator. Archive the analysis code in a versioned repository (GitHub + a Zenodo release DOI).","Cite the dataset in the reference list like a publication — creator, year, title, repository, DOI/accession — and cite it in-text where it is used. Only a reference- list entry is machine-readable to Crossref/DataCite, and only a citation lets the data earn credit. Cite the clinical / human-subjects repository accession (e.g. from dbGaP or the European Genome-phenome Archive (EGA)) in the reference list.","Version the deposit and cite the exact version analysed (a version-specific DOI, or an accession with its version suffix). A reader reproducing your work against 'the current release' is reproducing it against a different dataset."],"model":"deepseek/deepseek-v4-flash","agent_version":"fair_agent_v8","fulltext_source":"epmc_xml"},"fair_model":"deepseek/deepseek-v4-flash","fair_agent_version":"fair_agent_v8","fair_fulltext_source":"epmc_xml","fair_has_llm":true,"fair_computed_at":"2026-07-20T12:23:58.445241Z","clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}