Benefits
- Benefit
-
A 44.2% reduction in workload
Awaiting review
- Outcome identifiers
-
Unresolved
Not reviewedUnresolved
- Category
-
Improved Organizational Efficiency
Awaiting review
- Status
-
Reported benefit
Awaiting review
- Beneficiary groups
-
Organizations. People.
Awaiting review
- Beneficiaries
-
Unresolved
Not reviewedUnresolved
- Reach
-
Unresolved
Not reviewedUnresolved
- Distribution and access
-
Unresolved
Not reviewedUnresolved
- Duration
-
Unresolved
Not reviewedUnresolved
- Expected?
-
Yes
Awaiting review
- Costs and harms
-
Unresolved
Not reviewedUnresolved
AI system
- System
-
Transpara
Awaiting review
- Model
-
This is an explicit unresolved assignment: the sources on record do not settle this question.
Not reviewedUnresolved
- Reported configuration
-
Transpara version 1.7.0
Awaiting review
- Provider
-
Unresolved
Not reviewedUnresolved
- Role
-
Unresolved
Not reviewedUnresolved
- Configuration
-
Unresolved
Not reviewedUnresolved
- Inputs and outputs
-
Unresolved
Not reviewedUnresolved
- Autonomy
-
Unresolved
Not reviewedUnresolved
- Workflow
-
Transpara scores decided whether one or two radiologists read each examination. Radiologists saw the software's marks on suspicious findings.
Awaiting review
- Human oversight
-
Unresolved
Not reviewedUnresolved
- Relation to AI
-
Women were randomized by the picture archive system to AI-supported reading or standard double reading, so the trial isolates the AI-supported protocol. The protocol combines triage with detection marks, and the trial does not separate the two.
Awaiting review
- AI contribution
-
Women were randomized by the picture archive system to AI-supported reading or standard double reading, so the trial isolates the AI-supported protocol. The protocol combines triage with detection marks, and the trial does not separate the two.
Awaiting review
Measurement
- Studies
-
Randomized. [2]
Fully reviewed: supporting details for Studies
Review date: 29 October 2026.
Sources: [2]
- Study design
-
Randomized. [2]
Fully reviewed: supporting details for Study design
Review date: 29 October 2026.
Sources: [2]
- Measurement
-
Count of screen readings; cancer registry and pathology follow-up for detected and interval cancers. [2]
Fully reviewed: supporting details for Measurement
Review date: 29 October 2026.
Sources: [2]
- Setting and sample
-
105,934 women at four screening sites in southwest Sweden. [2]
Fully reviewed: supporting details for Setting and sample
Review date: 29 October 2026.
Sources: [2]
- Measures
-
Screen-reading workload; cancer detection rate; interval cancer rate. [2]
Fully reviewed: supporting details for Measures
Review date: 29 October 2026.
Sources: [2]
- Comparison
-
Standard double reading without AI. [2]
Fully reviewed: supporting details for Comparison
Review date: 29 October 2026.
Sources: [2]
- Results
-
44.2% fewer readings; detection 6.4 versus 5.0 per 1,000 (ratio 1.29). [2]
Fully reviewed: supporting details for Results
Review date: 29 October 2026.
Sources: [2]
- Additional value from AI
-
48,444 fewer screen readings. [2]
Fully reviewed: supporting details for Additional value from AI
Review date: 29 October 2026.
Sources: [2]
- Limitations
-
One region of Sweden, one vendor version; author interests not read in full text. [2]
Fully reviewed: supporting details for Limitations
Review date: 29 October 2026.
Sources: [2]
Money
- Kind of value
-
The kind of monetary value is unclear.
Not reviewedUnresolved
- Amount
-
The monetary value is not established.
Not reviewedUnresolved
- Currency and prices
-
The currency and price basis are unclear.
Not reviewedUnresolved
- Period and unit
-
The period and unit of the monetary estimate are unclear.
Not reviewedUnresolved
- Realization
-
Whether the monetary value was realized is unclear.
Not reviewedUnresolved
- Recipients and payers
-
The recipients and payers are unclear.
Not reviewedUnresolved
- Gross or net
-
Whether the monetary figure includes costs is unclear.
Not reviewedUnresolved
- Included costs
-
The costs included in the estimate are unclear.
Not reviewedUnresolved
- Comparison
-
The financial comparison is not established.
Not reviewedUnresolved
- Method
-
The method used to calculate monetary value is unclear.
Not reviewedUnresolved
- Return and payback
-
The return on investment or payback period is not established.
Not reviewedUnresolved
People and places
- Participants
-
Developer: ScreenPoint Medical. Operator: Swedish national breast screening programme at Skåne University Hospital and Unilabs mammography units (MASAI trial, Lund University).
Awaiting review
- Jurisdictions
-
Benefit: Four screening sites in southwest
Sweden: Malmö, Lund, Landskrona and Trelleborg. Developer: 
Netherlands. Operator: Sweden.Awaiting review
- Ownership and control
-
Unresolved
Not reviewedUnresolved
- Dependencies
-
Unresolved
Not reviewedUnresolved
- Cross-border connections
-
Unresolved
Not reviewedUnresolved
- Geopolitical implications
-
The geopolitical implications are unclear.
Not reviewedUnresolved
Follow-up
- Conditions for replication
-
A screening programme with standard double reading to replace. Radiologists act on the risk score and marks.
Awaiting review
- Replication attempts
-
1 follow-up entry. Benefit recurred: 1.
Awaiting review
- Later findings
-
1 January 2026. The interval cancer analysis found a non-inferior interval cancer rate and higher sensitivity with AI support.
Awaiting review
- Availability
-
Unresolved
Not reviewedUnresolved
- Institutional decision
-
A relevant institutional decision has not been established.
Not reviewedUnresolved
- Grounds
-
The grounds for an institutional decision are unclear.
Not reviewedUnresolved
- Action and result
-
The result of an institutional decision is not established.
Not reviewedUnresolved
- Success criterion
-
The criterion for a successful institutional decision is unclear.
Not reviewedUnresolved
Evidence
- Source numbers
-
AIBD-0613-source-0001–0003
Awaiting review
- Citations
-
Numbered references below.
Awaiting review
- Language
-
Unresolved
Not reviewedUnresolved
- Source relationships
-
Independent, Operator
Awaiting review
- Original evidence
-
Unresolved
Not reviewedUnresolved
- Access and versions
-
Unresolved
Not reviewedUnresolved
- Supported findings
-
Unresolved
Not reviewedUnresolved
- Evidence links
-
Unresolved
Not reviewedUnresolved
- Evidence strength
-
Independently studied. Sources: one independent peer-reviewed study and two peer-reviewed studies from the deployer. The cited evidence includes no finding by a regulator or court. [1] [2] [3]
- Missing evidence
-
Unresolved
Not reviewedUnresolved
Grades
- Assessed benefits
-
Organizations. People.
Awaiting review
- Depth
-
Organizations: 2. People: 2.
Awaiting review
- Reasons
-
Organizations: Screen-reading workload fell by 44.2% (61,248 against 109,692 readings). People: Cancer detection rose from 5.0 to 6.4 per 1,000 women screened, and sensitivity rose from 73.8% to 80.5%.
Awaiting review
- Observed or intended
-
Unresolved
Not reviewedUnresolved
- Rubric
-
Unresolved
Not reviewedUnresolved
- Assessor and date
-
Unresolved
Not reviewedUnresolved
- Alternative assessments
-
Unresolved
Not reviewedUnresolved
- Fill
-
Independently studied
Awaiting review
Entry details
- Kind
-
The case describes an evaluation or a study. Randomized, controlled, non-inferiority screening accuracy trial. [1]
Fully reviewed: supporting details for Kind
Review date: 29 October 2026.
Sources: [1]
- Related entries
-
No incident in the AI Incident Database snapshot of 26 October 2026 concerns the same kind of system harming the same kind of stakeholder.
Partly reviewedUnresolved: supporting details for Related entries
Compared with the incidents in the AI Incident Database snapshot of 26 October 2026.
- Field
-
Healthcare.
Awaiting review
- Purpose
-
Transpara is built to score mammograms for cancer risk and mark suspicious findings. Using its score to triage exams to single or double reading was the trial's way of cutting workload, which is a stated aim.
Awaiting review
- Dates
-
Observed: 7 December 2022. Updated: 29 October 2026.
Awaiting review
- Stage
-
The system was used in a pilot. AI-supported reading ran for half of screened women within a randomized trial in the national programme. [1]
Fully reviewed: supporting details for Stage
Review date: 29 October 2026.
Sources: [1]
- Version
-
SHA-256: e9785fcab484…
Awaiting review: supporting details for Version
SHA-256 of the public case, its assessments, and its displayed answers and notes, excluding its own identifier and the derived coverage summary.
References
- Other identifiers
-
Unresolved
Not reviewedUnresolved
- Category mappings
-
Unresolved
Not reviewedUnresolved
- Citable summary
-
Unresolved
Not reviewedUnresolved
- Revisions
-
1 revision. Latest: 29 October 2026.
Awaiting review
Sources
-
Peer-reviewed study Independent author
Ciurescu S, Buciu V, Ilaș DG, et al. Ten Years of Artificial Intelligence in Screening Mammography: A Systematic Review and Meta-Analysis of Diagnostic Accuracy and Clinical Implementation (Literature Published 2015-2025). Diagnostics 2026;16:3045. doi:10.3390/diagnostics16183045. Independent review by authors at Victor Babeș University, Timișoara.
with the MASAI randomised trial alone reporting 1.29 (1.09-1.51) and a 44% reduction in screen reading
-
Peer-reviewed study Deployer
Hernström V, Josefsson V, Sartor H, et al. Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study. Lancet Digital Health 2025;7(3):e175-e183. Written by Lund University and Skåne University Hospital radiologists who ran the screening; abstract read. Co-author Solveig Hofvind heads BreastScreen Norway at the Cancer Registry of Norway, which the authors declare has a research agreement with ScreenPoint Medical.
There were 61 248 screen readings in the intervention group and 109 692 in the control group, resulting in a 44·2% reduction in the screen-reading workload.
-
Peer-reviewed study Deployer
Gommers J, Hernström V, Josefsson V, et al. Interval cancer, sensitivity, and specificity comparing AI-supported mammography screening with standard double reading without AI in the MASAI study. The Lancet 2026. doi:10.1016/S0140-6736(25)02464-X. Abstract read. Co-author Solveig Hofvind heads BreastScreen Norway at the Cancer Registry of Norway, which the authors declare has a research agreement with ScreenPoint Medical.
Sensitivity was higher in the intervention group (80·5% [95% CI 76·4-84·2]) than the control group (73·8% [68·9-78·3]; p=0·031)