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Artificial Intelligence · AI-08

Extract faithful clinical timelines

Evaluate extraction of dated health events into a traceable timeline while preserving uncertainty and recorded context.

  • Synthetic records
  • Longitudinal benchmark
  • Nairobi + Lagos
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Scope & purpose

Connected scope

Use structured clinical events to prototype extraction of dates, encounters, conditions and timeline relationships.

  • Health
  • Demographics
  • Insurance

Assess identity, dates and factual support against the supplied records. Agree evaluation references before delivery.

Possible uses

Task prototyping · Evidence tracing · Error analysis · Controlled evaluation

Who it is for

Clinical NLP teams · health-AI labs · informatics researchers · evaluators

Preview type
Illustrative format preview
Shows example structure and fields. It is not a sample extracted from the paid release.
Commercial availability
Confirmed in your written quote
The listed cities describe catalogue coverage. We confirm the exact release and available extract before agreement.
Starting-price basis
USD per selected city
Cohort size and period are specified in the quote; the listed rate does not define a fixed-size package. Discount and tax are shown separately.
Your agreed delivery
Scope and supporting artifacts listed in the quote
Confirm entities or rows, observation period, fields, formats, documentation, evidence, known limits and usage rights.

Paid dataset delivery

What you receive

SD delivery standard
Published cities
Nairobi + Lagos
Record scope
Resident + encounter
Structure
Longitudinal benchmark

Striped Donkey delivery package

  • data/Agreed extract and formats
  • documentation/Schema, fields and relationships
  • evidence/Agreed release checks and limits
  • examples/Agreed loading and join examples
  • LICENSEApplicable rights
  • MANIFESTRelease and file inventory
  • CHECKSUMSSHA-256 fingerprints
  • DELIVERY_NOTEScope and handoff record

Your written quote confirms selected cities, period, formats, commercial rights, detailed artifacts and secure delivery. The complete paid package is prepared privately after agreement.

Free evaluation preview

Inspect before you request

15 illustrative rows · 11 fields · CSV

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Illustrative rows show the format. Your quote confirms delivered records, fields and time coverage.

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Fields and record structure

Listed features

Resident + encounter · Longitudinal benchmark

  • dated encounters
  • care history
  • health-state events
  • age / life stage
  • household relationships
  • dated demographic events
  • coverage context

Study question

Evaluation design

Can an AI extract and order dated clinical events into a source-linked timeline while preserving uncertain dates and distinguishing separate events from duplicates?

Evaluate event and date extraction, ordering, source attribution and duplicate handling; define the input format and reference timeline before scoring.

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Evidence you can inspect

Source & limitations

Review release-specific methods and published checks. Preview rows show format and scope; they do not certify a dataset.

Supporting references
NairobiEvidenceSamples
LagosEvidenceSamples
MethodsGenerationReproduce

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Licence & delivery

Free preview

Use free samples under the public-use policy or their dataset-specific licence. Attribution is required for publication and research outputs.

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Purchased dataset

Your agreement defines the release, licensed organization, permitted uses and duration. Commercial model training, external applications and redistribution require explicit agreement.

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