Evidence map›Paper›PMID 42866596›Full record

ReviewESMO real world data and digital oncology2026

Leveraging artificial intelligence to strengthen cancer care in Belgium: a policy brief from the Belgian Europe's Beating Cancer Plan Mirror Group.

E Cauët, R Saesen, M Van Den Bulcke, Thematic Working Group ‘Data, Innovation, and Artificial Intelligence’ of the Belgian Europe’s Beating Cancer Plan Mirror Group†, El Maâti Allaoui, Hélène Antoine-Poirel, Sarah Baatout, Lieve Brochez, Frederik Deman, Harlinde De Schutter and 11 more

Abstract readReview
In one paragraph

Review in ESMO real world data and digital oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

E CauëtBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
R SaesenBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
M Van Den BulckeBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Thematic Working Group ‘Data, Innovation, and Artificial Intelligence’ of the Belgian Europe’s Beating Cancer Plan Mirror Group†
El Maâti AllaouiBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Hélène Antoine-PoirelBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Sarah BaatoutBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Lieve BrochezBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Frederik DemanBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Harlinde De SchutterBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Stefanie DevosBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Piet DirixBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Benoit ErnstBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Gokhan ErtaylanBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Julien GuiotBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Koen HasaersBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Barbara PlehiersBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Roberto SalgadoBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Arezki SemrouniBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Ad VandermeulenBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Lien Van De VoordeBelgian Cancer Centre, Department of Epidemiology and Public Health, Sciensano, Brussels, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is transforming health care, especially oncology, by enhancing early cancer detection and screening, diagnosis, treatment, patient monitoring, and research. Despite strong research activity, AI adoption in clinical practice in Belgium remains limited due to resource constraints, regulatory complexity, and fragmented governance. Belgium should act decisively now to ensure that it does not miss the opportunity to lead in responsible and effective AI integration in health care. Building on the European Union's AI Continent Action Plan, now is the time to define a coordinated national strategy, one that can turn AI's potential into real benefits for patients and health care systems across the country.

Indexed as

artificial intelligencedata infrastructurehealth carenational strategyoncologyregulation

Identifiers

PMID42866596
PMCPMC13656972

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.