{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T22:07:20Z","timestamp":1781215640959,"version":"3.54.1"},"reference-count":71,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T00:00:00Z","timestamp":1685491200000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Minister of Economy and Competitiveness of Spain","award":["PID2019-110344RB-I00"],"award-info":[{"award-number":["PID2019-110344RB-I00"]}]},{"name":"PIBA Programme of the Basque Government","award":["PIBA_2020_01_0055"],"award-info":[{"award-number":["PIBA_2020_01_0055"]}]},{"name":"Elkartek programme of the Basque Government","award":["KK-2020\/00008"],"award-info":[{"award-number":["KK-2020\/00008"]}]},{"DOI":"10.13039\/501100000289","name":"Cancer Research UK","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000289","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Accelerator Award Programme","award":["C355\/A26819"],"award-info":[{"award-number":["C355\/A26819"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Great efforts have been made to develop precision medicine-based treatments using machine learning. In this field, where the goal is to provide the optimal treatment for each patient based on his\/her medical history and genomic characteristics, it is not sufficient to make excellent predictions. The challenge is to understand and trust the model\u2019s decisions while also being able to easily implement it. However, one of the issues with machine learning algorithms\u2014particularly deep learning\u2014is their lack of interpretability. This review compares six different machine learning methods to provide guidance for defining interpretability by focusing on accuracy, multi-omics capability, explainability and implementability. Our selection of algorithms includes tree-, regression- and kernel-based methods, which we selected for their ease of interpretation for the clinician. We also included two novel explainable methods in the comparison. No significant differences in accuracy were observed when comparing the methods, but an improvement was observed when using gene expression instead of mutational status as input for these methods. We concentrated on the current intriguing challenge: model comprehension and ease of use. Our comparison suggests that the tree-based methods are the most interpretable of those tested.<\/jats:p>","DOI":"10.1093\/bib\/bbad200","type":"journal-article","created":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T05:15:20Z","timestamp":1685510120000},"source":"Crossref","is-referenced-by-count":15,"title":["Precision oncology: a review to assess interpretability in several explainable methods"],"prefix":"10.1093","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0756-3055","authenticated-orcid":false,"given":"Marian","family":"Gimeno","sequence":"first","affiliation":[{"name":"Departamento de Ingenier\u00eda Biom\u00e9dica y Ciencias, TECNUN, Universidad de Navarra , 20009, San Sebasti\u00e1n , Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7634-7962","authenticated-orcid":false,"given":"Katyna","family":"Sada del Real","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Biom\u00e9dica y Ciencias, TECNUN, Universidad de Navarra , 20009, San Sebasti\u00e1n , Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3274-2450","authenticated-orcid":false,"given":"Angel","family":"Rubio","sequence":"additional","affiliation":[{"name":"Departamento de Ingenier\u00eda Biom\u00e9dica y Ciencias, TECNUN, Universidad de Navarra , 20009, San Sebasti\u00e1n , Spain"},{"name":"Instituto de Ciencia de los Datos e Inteligencia Artificial (DATAI), Universidad de Navarra , 31008, Pamplona , Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,5,30]]},"reference":[{"key":"2023072020034921500_ref1","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1038\/nrg.2016.86","article-title":"Towards precision medicine","volume":"17","author":"Ashley","year":"2016","journal-title":"Nat Rev 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