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<p>Molecular tumor boards are supported by clinical decision support system (CDSS) tools for the interpretation of complex molecular data towards personalized treatments. Current CDSS tools are genomics-focused and characterized by tight couplings between data ingestion, guideline-based reasoning logic and curated knowledgebases. Next-generation CDSS solutions should integrate multimodal data and learn from outcomes in an interoperable ecosystem, leveraging explainable, trustworthy output from AI models through rigorous clinical validation processes.</p>

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Towards an ecosystem of clinical decision support tools for precision cancer medicine

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月17日

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  • Sigve Nakken,
  • Anders Edsjö,
  • Janne Lehtiö,
  • Vigdis Nygaard,
  • Paul Roepman,
  • Richard Rosenquist,
  • Hege G. Russnes,
  • Albrecht Stenzinger,
  • David Tamborero,
  • Sen Zhao,
  • Agnieszka Janowska,
  • Alba López Rioja,
  • Anni Lepland,
  • Antonio Marra,
  • Anu Ustav,
  • Åslaug Helland,
  • Attila Patocs,
  • Beatrice Mainoli,
  • Bettina Ryll,
  • Birute Brasiuniene,
  • Daniel Kazdal,
  • Ebba Hallersjö Hult,
  • Edita Baltruškevičienė,
  • Eduard Vrdoljak,
  • Egbert Smit,
  • Eivind Hovig,
  • Elena Chavarria,
  • Elena Garralda,
  • Eline Aas,
  • Elisa Bjørgo,
  • Giuseppe Curigliano,
  • Gro Live Fagereng,
  • Hans Gelderblom,
  • Hans Timmer,
  • Hege G. Russnes,
  • Henk Verheul,
  • Henriett Butz,
  • Irene Brana,
  • Iwona Lugowska,
  • Izabela Agnieszczak,
  • Jean-Yves Blay,
  • Julio Oliveira,
  • Kadri Rekker,
  • Kadri Toome,
  • Katriina Jalkanen,
  • Kjetil Taskén,
  • Knut Smeland,
  • Kristoffer Staal Rohrberg,
  • Loic Verlingue,
  • Martin Højgaard,
  • Mika Mustonen,
  • Paola Zagami,
  • Ragnhild Sørum Falk,
  • Rasa Sabaliauskaite,
  • Richard Rosenquist,
  • Rui Henrique,
  • Sahar Barjesteh van Waalwijk van Doorn-Khosrovani,
  • Sigmund Brabrand,
  • Simon Ekman,
  • Soemeya F. Haj Mohammad,
  • Sonata Jarmalaite,
  • Tanja Juslin,
  • Tiina Kahre,
  • Tina Kringelbach,
  • Tormod Guren,
  • Ulrik Lassen,
  • Vigdis Nygaard,
  • Vince Kornél Grolmusz,
  • Eivind Hovig

摘要

Molecular tumor boards are supported by clinical decision support system (CDSS) tools for the interpretation of complex molecular data towards personalized treatments. Current CDSS tools are genomics-focused and characterized by tight couplings between data ingestion, guideline-based reasoning logic and curated knowledgebases. Next-generation CDSS solutions should integrate multimodal data and learn from outcomes in an interoperable ecosystem, leveraging explainable, trustworthy output from AI models through rigorous clinical validation processes.