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Radiology AI
Evaluate report understanding, finding extraction, structured outputs and suitable image-plus-report tasks when the required cohort and reference criteria are available.
Reports + selected DICOM cohortsHealthcare data · AI evaluation · Intelligence
Powering Trusted Healthcare & Enterprise AI
Datavendor brings together 500K+ clinical and radiology report records, multi-modality DICOM imaging studies, and associated study reports where available — supporting healthcare AI development, evaluation and benchmarking.
Cohort availability, report/image linkage and data fields are confirmed for each request.
HealthcareRadiology, pathology, laboratory and clinical reports
DICOMMultiple imaging modalities; report links confirmed per cohort
EnterpriseData inventory, workforce timesheets and transactions
AI EvaluationClinical AI validation and benchmarking in development
New capability
Clinical AI Validation & Benchmarking
We are developing project-scoped evaluation workflows to help healthcare AI teams test how their models perform on curated clinical reports and suitable DICOM/report cohorts — and understand where errors or inconsistencies occur.
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Pathology AI
Assess pathology report classification, diagnosis/finding extraction and report structuring for agreed tasks and curated reference subsets.
Pathology reports🧪
Laboratory & Clinical NLP
Evaluate lab result extraction, clinical entity recognition, structured data generation and summarization where suitable references exist.
Clinical text🤖
Medical LLM Evaluation
Review task performance, consistency, unsupported statements, omissions and hallucination-related failure patterns against agreed references.
LLM benchmarking📈
Robustness & Error Analysis
Compare results across defined report types, wording patterns, clinical domains and metadata-supported subgroups.
Failure analysis📑
Evidence-led Reports
Produce project-specific summaries of methods, metrics, limitations and recurring errors, with clinical review included when required.
Scoped evaluationEvaluation integrity: a clinical report is not automatically a gold-standard label. Reference labels, paired-image suitability and review requirements must be agreed for each task. This capability is being developed and project scope is confirmed case by case.
Data portfolio
Clinical & imaging data portfolio
Explore clinical reports and DICOM cohorts for AI development, research and evaluation. Available volumes, metadata, report linkage and licensing are confirmed during cohort review.
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Clinical & Radiology Reports
Curated report collections across radiology and other clinical domains. Available fields and specialty mix are confirmed for each request.
Report collections🧠
DICOM Imaging Studies
Multiple imaging study types, including cohorts across available modalities such as CT, MRI, X-ray and ultrasound. Exact inventory is shared on request.
DICOM🔗
Imaging + Study Reports
Study reports and corresponding DICOM data are available for eligible matched cohorts. Patient/study linkage and metadata completeness are checked per request.
Paired data where available🔬
Pathology Reports
Pathology report collections for suitable information extraction, classification, report-understanding and research tasks, subject to cohort review.
Pathology🧪
Laboratory & Clinical Records
Laboratory result profiles and structured clinical records for agreed analytics, extraction and AI evaluation use cases.
Clinical data🧬
Oncology & Disease-specific Cohorts
Specialized collections may be available for particular clinical research or evaluation requirements; suitability is reviewed case by case.
Specialized cohortsEnterprise data portfolio
De-identified data for business intelligence & enterprise AI
Alongside healthcare data, Datavendor offers enterprise datasets covering data inventories, workforce timesheets and real-world business transactions; all are de-identified before sharing. Schema, fields, date range, coverage and licensing are confirmed for each collection.
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Enterprise Data Inventory & Persona-Based Data Footprint
Enterprise data inventory and persona-based data footprint records to help map data assets to documented business roles, personas and intended use. Scope and schema are confirmed per collection.
Inventory & persona mapping🕒
Workforce & Timesheet Data
Company-wide employee timesheet records, with employee identities de-identified before sharing. Available time-entry and workforce attributes depend on the source schema and agreed scope.
Workforce analytics💼
Enterprise Transaction Dataset
De-identified real-world operational data covering actual sales, invoices, orders and financial transactions for agreed business analytics and enterprise AI use cases.
Real-world transaction dataDV MedAI
COMING SOONDatavendor’s planned Clinical Intelligence Engine. DV MedAI is in development, with a focus on bringing clinical data search, report understanding, evidence-linked exploration and AI-assisted research workflows into a unified platform. Product scope and availability will be announced as development progresses.
UnderstandClinical reports
SearchClinical information
EvaluateAI model outputs
ExplainEvidence-led insight
How we work
From data to measurable evaluation
A clear, task-specific process keeps each project grounded in dataset quality, suitable references and agreed success measures.
STEP 01
Define the use case
Agree model, task, inputs, outputs and evaluation criteria.
STEP 02
Review the cohort
Confirm modality, reports, linkage, metadata and permissions.
STEP 03
Curate references
Check quality and define reference/clinical-review needs.
STEP 04
Evaluate the model
Compare predictions with agreed references and metrics.
STEP 05
Explain the results
Report performance, limitations and error patterns.
Why Datavendor
Data and evaluation, built around the use case
We focus on matching a dataset to the task — including report coverage, image/report linkage, available labels, metadata completeness and permitted use — before proposing an evaluation design.
Dataset-specific review
Scope and data fields are discussed before sample selection or evaluation.
Clinical domain breadth
Radiology, pathology, laboratory and other clinical reports, plus DICOM cohorts where available.
Transparent methodology
Evaluation findings are reported alongside methodology, limitations and reference-quality considerations.
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Privacy & Data Handling
Clinical data de-identification follows the HIPAA Safe Harbor method; enterprise datasets are de-identified before sharing.
Privacy-focused handlingContact Datavendor
Tell us what you are building
Ask about report collections, DICOM and linked study-report cohorts, clinical AI validation or the upcoming DV MedAI platform.
Talk to our team
Share your AI use case, required data types, model task, expected cohort size and target timeline.
Email Datavendor