Research map: Bridging the AI chasm in oncology: a standardized platform to enable the in silico clinical validation of AI models within the CHAIMELEON Project

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  1. SUS: A 'Quick and Dirty' Usability Scale · john Brooke · 1996 · 8199 citations · Cited by this paper
  2. Towards an accessible, centralised, searchable database for AI courses in Europe: the Artificial Intelligence in Medical Imaging and Radiation Oncology Education (AIMIROE) project · 2026 · Related
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  15. The Orthanc Ecosystem for Medical Imaging · Sébastien Jodogne · 2018 · 90 citations · Cited by this paper
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  17. Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects · Haridimos Kondylakis · 2023 · 88 citations · Cited by this paper
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  19. Impact of AI on radiology: a EuroAIM/EuSoMII 2024 survey among members of the European Society of Radiology · Moreno Zanardo · 2024 · 61 citations · Cited by this paper
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  21. Credibility assessment of in silico clinical trials for medical devices · Pras Pathmanathan · 2024 · 55 citations · Cited by this paper
  22. ESR Essentials: radiomics—practice recommendations by the European Society of Medical Imaging Informatics · João Santinha · 2024 · 49 citations · Cited by this paper
  23. How many testers are needed to assure the usability of medical devices? · Simone Borsci · 2014 · 46 citations · Cited by this paper
  24. Bridging gaps between images and data: a systematic update on imaging biobanks · Michela Gabelloni · 2022 · 41 citations · Cited by this paper
  25. CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools · Luis Martí‐Bonmatí · 2022 · 41 citations · Cited by this paper
  26. Dimensions of ecological validity for usability evaluations in clinical settings · Niels van Berkel · 2020 · 38 citations · Cited by this paper
  27. Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure · Luis Martí‐Bonmatí · 2025 · 30 citations · Cited by this paper
  28. Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks · Haridimos Kondylakis · 2022 · 29 citations · Cited by this paper
  29. A Review on Identity and Access Management Server (KeyCloak) · D. N. Divyabharathi · 2020 · 27 citations · Cited by this paper
  30. An exploration of expectations and perceptions of practicing physicians on the implementation of computerized clinical decision support systems using a Qsort approach · Wim Van Biesen · 2022 · 24 citations · Cited by this paper
  31. Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images · Diana Veiga-Canuto · 2023 · 23 citations · Cited by this paper
  32. Development of imaging biomarkers and generation of big data · Ángel Alberich‐Bayarri · 2017 · 21 citations · Cited by this paper
  33. Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap! · Ioanna Chouvarda · 2025 · 16 citations · Cited by this paper
  34. Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors · Diana Veiga-Canuto · 2024 · 8 citations · Cited by this paper
  35. Medical Imaging Processing Architecture on ATMOSPHERE Federated Platform · Ignácio Blanquer · 2019 · 5 citations · Cited by this paper
  36. Trustworthy AI in Cancer Imaging Research · Ioanna Chouvarda · 2025 · 2 citations · Cited by this paper
  37. How the First Medical Imaging Cancer Atlas EUCAIM Was Populated: The Experience of a Reference Hospital. · Ana Penadés Blasco · 2025 · 2 citations · Cited by this paper
  38. A cloud infrastructure for scalable computing on population imaging databanks · Ignácio Blanquer · 2015 · 1 citation · Cited by this paper
  39. Empowering imaging research through the EUCAIM repository: a new opportunity for ESR journals’ authors · Luis Martí‐Bonmatí · 2025 · 1 citation · Cited by this paper

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