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Helping GPs to extrapolate guideline recommendations to patients for whom there are no explicit recommendations, through the visualization of drug properties. The example of AntibioHelp® in bacterial diseases., , , , , , , and . J. Am. Medical Informatics Assoc., 26 (10): 1010-1019 (2019)Implementation of an ontological reasoning to support the guideline-based management of primary breast cancer patients in the DESIREE project., , , , , , , and . Artif. Intell. Medicine, (2020)Using data mining techniques to explore physicians' therapeutic decisions when clinical guidelines do not provide recommendations: methods and example for type 2 diabetes., , , and . BMC Medical Informatics Decis. Mak., (2009)Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies. Artificial Intelligence in Medicine, (2017)A generic system for critiquing physicians' prescriptions: usability, satisfaction and lessons learnt., , , , , , , and . CoRR, (2013)Explainable decision support through the learning and visualization of preferences from a formal ontology of antibiotic treatments., , and . J. Biomed. Informatics, (2020)ABiMed: An intelligent and visual clinical decision support system for medication reviews and polypharmacy management., , , , , , , , , and 7 other author(s). CoRR, (2023)A New Diagram for Amino Acids: User Study Comparing Rainbow Boxes to Venn/Euler Diagram.. IV, page 561-566. IEEE Computer Society, (2018)Intelligence artificielle explicable pour le cancer du sein : Une approche visuelle de raisonnement à partir de cas., , , , and . EGC, volume E-36 of RNTI, page 457-466. Éditions RNTI, (2020)Learning Preferences in Lexicographic Choice Logic., , , and . ICAART (3), page 1012-1019. SCITEPRESS, (2023)