AI-Assisted Extraction of Clinical Trial Data from Research Articles

Research & Development

What it collects

Operational data

Anonymized data

Full-text scientific journal articles reporting randomized controlled trials. These are published academic documents, not personal data. The system processes the textual content of these articles to identify and extract trial characteristics.

Government of Canada AI Register — ExaCT

Run by: National Research Council Canada (NRC)
Where: No fixed location
Kept: Not stated by the Helpful Places.
Shared with: Not stated by the Helpful Places.
Your copy: You cannot see the data it holds about you. What you can do

What it is for

Research & Development

ExaCT is an automated system that helps medical researchers and clinicians find and extract key information about randomized controlled trials from published journal articles. It is designed to speed up the labour-intensive process of compiling evidence for systematic reviews and meta-analyses. The system has been retired and no longer processes new material. Users were informed that AI was involved in the extraction process.

What it collects and what happens to it

Data taken in

Operational data

Anonymized data

Full-text scientific journal articles reporting randomized controlled trials. These are published academic documents, not personal data. The system processes the textual content of these articles to identify and extract trial characteristics.

Government of Canada AI Register — ExaCT

Processing

Classification & Prediction

ExaCT uses information extraction techniques to classify and locate specific elements within clinical trial articles — such as trial design, intervention, comparator, outcomes, and population characteristics — automating what would otherwise require manual review by trained reviewers.

Government of Canada AI Register — ExaCT

What it does

Deciding (Analytical AI)

Human decides

ExaCT classifies and extracts structured information from free-text journal articles, identifying key characteristics of randomized controlled trials. Researchers and clinicians review and verify the extracted information — ExaCT assists but does not make final decisions.

Government of Canada AI Register — ExaCT

Outputs

Operational data

Anonymized data

Structured extractions of key characteristics from randomized controlled trial articles — such as trial design elements, interventions, populations, and outcomes — presented to researchers for review and use in evidence synthesis studies. No personal information is included in the output.

Government of Canada AI Register — ExaCT

Run by

National Research Council Canada (NRC)

The National Research Council Canada (NRC) developed and deployed ExaCT to assist medical researchers and clinicians with information extraction from clinical trial literature.

Government of Canada AI Register — ExaCT

Built by

Not stated by the Helpful Places.

Kept for

Not stated by the Helpful Places.

Shared with

Not available to me

ExaCT does not collect or process personal information. The system has been retired and is no longer in operation, so no data produced by the system is currently accessible.

Government of Canada AI Register — ExaCT

Stored

Not stated by the Helpful Places.

How to read the colours

Can it identify you?

Anonymized data: Data about people with the link to who is broken. Stripped of identifiers, blurred, aggregated, or noised so this system can’t reasonably tie a record back to an individual.
Pseudonymous data: Each person’s data is tied to a token (hash, ID, template) that lets this system recognise the same person across events, but the token itself doesn’t reveal a name. Reidentification is possible with extra information.
Identifiable data: The data either contains a direct identifier (name, address, account name, recognisable face or voice, plate number) or carries a token this system uses to look up legal identity during processing.

Who completes the loop?

Human decides: This mode suggests; a person decides what to do next. The AI is always advisory — a human is in the loop on every decision. Example: a triage tool ranks cases for a clinician who chooses which to see first.
Human executes: This mode decides; a person carries out the result. Example: an optimizer plans the day’s trash-collection routes, and drivers run them.
Autonomous: This mode decides and acts on its own. No person reviews each decision or carries out the resulting action.

Definitions from the DTPR standard. Amber is about your data, violet about who decides. The fuller the shape and the deeper the colour, the more identifying the data or the less a person is involved.

What you can do

Ask about this system

Questions go to the Helpful Places, not the vendor.

Your rights

Right to Algorithmic TransparencyUsers were informed that AI was involved in the information extraction process. As a research tool operated by the National Research Council Canada and now retired, further inquiries about the system's methodology can be directed to the NRC.

Risks and safeguards

No risks or safeguards have been published for this system yet.