Evidence map›Paper›PMID 41923228›Full record

ArticleBMC proceedings2026

Multimodal AI-driven analysis in breast and lung cancer: insights from the OPTIMA prototyping workshop.

Maryam Abdollahyan, Emanuela Gadaleta, Lewis G E James, Graeme J Thorn, Javier Cuadrado Corz, Vivek Singh, Manuel Hettich, Lisa Schneider, Oscar Maiques, Ayman Hijazy and 12 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC proceedings, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

22 authors.

Maryam AbdollahyanCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Emanuela GadaletaCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Lewis G E JamesCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Graeme J ThornCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Javier Cuadrado CorzCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Vivek SinghCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Manuel HettichLudwig Maximilian University of Munich, Munich, Germany.
Lisa SchneiderR&D Machine Learning Research, Bayer AG Pharmaceuticals Division, Berlin, Germany.
Oscar MaiquesCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK.
Ayman HijazyOdysseus Data Services, an EPAM Company, New York, NY, USA.
Asieh GolozarOdysseus Data Services, an EPAM Company, New York, NY, USA.
Juan Gómez RivasDepartment of Urology, Hospital Clinico San Carlos, Madrid, Spain.
Philip CornfordLiverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
Rossella NicolletiUnit of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, Florence, Italy.
Thomas AbbottEuropean Association of Urology Guidelines Office, Arnhem, The Netherlands.
Eng Hooi TanCentre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Danielle NewbyCentre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Giorgos PapanastasiouArtificial Intelligence Data and Analytics, Pfizer Inc, New York, NY, USA.
Michael BussmannHelmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany.
Bertrand De MeulderEuropean Association of Urology Guidelines Office, Arnhem, The Netherlands.
Claude ChelalaCentre for Cancer Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, London, UK. c.chelala@qmul.ac.uk.
PIONEER consortium and the OPTIMA consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper reports on insights from the OPTIMA (Optimal Treatment for Patients with Solid Tumours in Europe Through Artificial Intelligence) prototyping workshop held in Berlin from November 6 to November 8, 2024. Through integrated analysis of clinical, genomic, imaging and pathology data, we addressed the following key challenges in breast and lung cancer management: utility of comprehensive genomic profiling in metastatic breast cancer settings; relevance of tumor heterogeneity for predicting treatment response; development of less invasive technologies for assessing tumor biology; and treatment outcomes in early stages of small cell lung cancer. Our findings demonstrate the potential of computational analysis using multiple data modalities to identify cancer molecular subtypes and enhance treatment selection and monitoring while highlighting important areas for future development to achieve the research objectives of the OPTIMA consortium.

Indexed as

Artificial IntelligenceBreast cancerLung cancerOptimal treatment

Identifiers

PMID41923228
PMCPMC13045054

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.