{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T11:40:03Z","timestamp":1750592403340,"version":"3.41.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031958373","type":"print"},{"value":"9783031958380","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-95838-0_1","type":"book-chapter","created":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T11:14:17Z","timestamp":1750590857000},"page":"1-10","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Combining Clinical and Gene Expression Variables via Knowledge Graph Embedding for Prediction of Coronary Artery Stenosis"],"prefix":"10.1007","author":[{"given":"Giuseppe","family":"Albi","sequence":"first","affiliation":[]},{"given":"Arianna","family":"Dagliati","sequence":"additional","affiliation":[]},{"given":"Chiara","family":"Vavassori","sequence":"additional","affiliation":[]},{"given":"Laura","family":"Pisani","sequence":"additional","affiliation":[]},{"given":"Mattia","family":"Chiesa","sequence":"additional","affiliation":[]},{"given":"Luca","family":"Piacentini","sequence":"additional","affiliation":[]},{"given":"Saima","family":"Mushtaq","sequence":"additional","affiliation":[]},{"given":"Gianluca","family":"Pontone","sequence":"additional","affiliation":[]},{"given":"Riccardo","family":"Bellazzi","sequence":"additional","affiliation":[]},{"given":"Gualtiero I.","family":"Colombo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,23]]},"reference":[{"key":"1_CR1","doi-asserted-by":"publisher","first-page":"3415","DOI":"10.1093\/eurheartj\/ehae177","volume":"45","author":"C Vrints","year":"2024","unstructured":"Vrints, C., et al.: ESC scientific document group: 2024 ESC guidelines for the management of chronic coronary syndromes: developed by the task force for the management of chronic coronary syndromes of the European Society of Cardiology (ESC) endorsed by the European Association for Cardio-Thoracic Surgery (EACTS). Eur. Heart J. 45, 3415\u20133537 (2024)","journal-title":"Eur. Heart J."},{"key":"1_CR2","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1080\/10408363.2016.1241214","volume":"54","author":"D Navas-Carrillo","year":"2017","unstructured":"Navas-Carrillo, D., Mar\u00edn, F., Vald\u00e9s, M., Orenes-Pi\u00f1ero, E.: Deciphering acute coronary syndrome biomarkers: High-resolution proteomics in platelets, thrombi and microparticles. Crit. Rev. Clin. Lab. Sci. 54, 49\u201358 (2017)","journal-title":"Crit. Rev. Clin. Lab. Sci."},{"key":"1_CR3","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1152\/physiolgenomics.00130.2011","volume":"44","author":"R Joehanes","year":"2012","unstructured":"Joehanes, R., et al.: Gene expression analysis of whole blood, peripheral blood mononuclear cells, and lymphoblastoid cell lines from the Framingham Heart Study. Physiol. Genomics 44, 59\u201375 (2012)","journal-title":"Physiol. Genomics"},{"key":"1_CR4","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1038\/s41551-022-00942-x","volume":"6","author":"MM Li","year":"2022","unstructured":"Li, M.M., Huang, K., Zitnik, M.: Graph representation learning in biomedicine and healthcare. Nat. Biomed. Eng. 6, 1353\u20131369 (2022)","journal-title":"Nat. Biomed. Eng."},{"key":"1_CR5","doi-asserted-by":"publisher","first-page":"494","DOI":"10.1109\/TNNLS.2021.3070843","volume":"33","author":"S Ji","year":"2022","unstructured":"Ji, S., Pan, S., Cambria, E., Marttinen, P., Yu, P.S.: A survey on knowledge graphs: representation, acquisition, and applications. IEEE Trans. Neural Netw. Learn. Syst. 33, 494\u2013514 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1_CR6","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1038\/s41597-023-01960-3","volume":"10","author":"P Chandak","year":"2023","unstructured":"Chandak, P., Huang, K., Zitnik, M.: Building a knowledge graph to enable precision medicine. Sci Data. 10, 67 (2023)","journal-title":"Sci Data."},{"key":"1_CR7","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.3390\/biomedicines10061309","volume":"10","author":"D Andreini","year":"2022","unstructured":"Andreini, D., et al.: Whole-blood transcriptional profiles enable early prediction of the presence of coronary atherosclerosis and high-risk plaque features at coronary CT angiography. Biomedicines 10, 1309 (2022)","journal-title":"Biomedicines"},{"key":"1_CR8","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1093\/bioinformatics\/btr597","volume":"28","author":"DJ Stekhoven","year":"2012","unstructured":"Stekhoven, D.J., B\u00fchlmann, P.: MissForest\u2014non-parametric missing value imputation for mixed-type data. Bioinformatics 28, 112\u2013118 (2012)","journal-title":"Bioinformatics"},{"key":"1_CR9","doi-asserted-by":"publisher","first-page":"1416","DOI":"10.1093\/bioinformatics\/btx795","volume":"34","author":"M Chiesa","year":"2018","unstructured":"Chiesa, M., Colombo, G.I., Piacentini, L.: DaMiRseq\u2014an R\/Bioconductor package for data mining of RNA-Seq data: normalization, feature selection and classification. Bioinformatics 34, 1416\u20131418 (2018)","journal-title":"Bioinformatics"},{"key":"1_CR10","unstructured":"Bordes, A., Usunier, N., Garcia-Dur\u00e1n, A., Weston, J., Yakhnenko, O.: Translating embeddings for modeling multi-relational data. In: Proceedings of the 26th International Conference on Neural Information Processing Systems, vol. 2, pp. 2787\u20132795. Curran Associates Inc., Red Hook (2013)"},{"key":"1_CR11","unstructured":"Yang, B., Yih, W., He, X., Gao, J., Deng, L.: Embedding entities and relations for learning and inference in knowledge bases. Presented at the International Conference on Learning Representations, 19 December 2014"},{"key":"1_CR12","unstructured":"Trouillon, T., Welbl, J., Riedel, S., Gaussier, E., Bouchard, G.: Complex embeddings for simple link prediction. In: Proceedings of the 33rd International Conference on Machine Learning, pp. 2071\u20132080. PMLR (2016)"},{"key":"1_CR13","unstructured":"Sun, Z., Deng, Z.-H., Nie, J.-Y., Tang, J.: RotatE: knowledge graph embedding by relational rotation in complex space. Presented at the International Conference on Learning Representations, 27 September 2018"},{"key":"1_CR14","doi-asserted-by":"crossref","unstructured":"Dettmers, T., Minervini, P., Stenetorp, P., Riedel, S.: Convolutional 2D knowledge graph embeddings. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 32 (2018)","DOI":"10.1609\/aaai.v32i1.11573"},{"key":"1_CR15","unstructured":"Ali, M., Berrendorf, M., Hoyt, C.T., Vermue, L., Sharifzadeh, S., Tresp, V., Lehmann, J.: PyKEEN 1.0: a python library for training and evaluating knowledge graph embeddings. J. Mach. Learn. Res. 22, 1\u20136 (2021)"},{"key":"1_CR16","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. In: Proceedings of the 3rd International Conference on Learning Representations (ICLR), Poster (2014)"},{"key":"1_CR17","doi-asserted-by":"crossref","unstructured":"Zhang, X.A., et al.: Semantic integration of clinical laboratory tests from electronic health records for deep phenotyping and biomarker discovery. NPJ Digit. Med. 2, 32 (2019)","DOI":"10.1038\/s41746-019-0110-4"},{"key":"1_CR18","unstructured":"Pagana, K.D., Pagana, T.J., Pagana, T.N.: Mosby\u2019s Diagnostic and Laboratory Test Reference-E-Book. Elsevier Health Sciences (2014)"},{"key":"1_CR19","doi-asserted-by":"crossref","unstructured":"Broadhead, W.E., Gehlbach, S.H., de Gruy, F.V., Kaplan, B.H.: The duke-UNC functional social support questionnaire. Measurement of social support in family medicine patients. Med. Care. 26, 709\u2013723 (1988)","DOI":"10.1097\/00005650-198807000-00006"},{"key":"1_CR20","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1046\/j.1525-1497.2001.016009606.x","volume":"16","author":"K Kroenke","year":"2001","unstructured":"Kroenke, K., Spitzer, R.L., Williams, J.B.: The PHQ-9: validity of a brief depression severity measure. J. Gen. Intern. Med. 16, 606\u2013613 (2001)","journal-title":"J. Gen. Intern. Med."},{"key":"1_CR21","doi-asserted-by":"publisher","first-page":"e43134","DOI":"10.1371\/journal.pone.0043134","volume":"7","author":"MA Mart\u00ednez-Gonz\u00e1lez","year":"2012","unstructured":"Mart\u00ednez-Gonz\u00e1lez, M.A., et al.: PREDIMED study investigators: A 14-item mediterranean diet assessment tool and obesity indexes among high-risk subjects: the PREDIMED trial. PLoS ONE 7, e43134 (2012)","journal-title":"PLoS ONE"},{"key":"1_CR22","doi-asserted-by":"publisher","first-page":"1241","DOI":"10.1111\/bph.14778","volume":"177","author":"L Schwingshackl","year":"2020","unstructured":"Schwingshackl, L., Morze, J., Hoffmann, G.: Mediterranean diet and health status: active ingredients and pharmacological mechanisms. Br. J. Pharmacol. 177, 1241\u20131257 (2020)","journal-title":"Br. J. Pharmacol."},{"key":"1_CR23","doi-asserted-by":"publisher","first-page":"3866","DOI":"10.21037\/jtd.2020.02.47","volume":"12","author":"G Gallucci","year":"2020","unstructured":"Gallucci, G., Tartarone, A., Lerose, R., Lalinga, A.V., Capobianco, A.M.: Cardiovascular risk of smoking and benefits of smoking cessation. J. Thorac. Dis. 12, 3866\u20133876 (2020)","journal-title":"J. Thorac. Dis."},{"key":"1_CR24","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"1_CR25","doi-asserted-by":"publisher","first-page":"861","DOI":"10.21105\/joss.00861","volume":"3","author":"L McInnes","year":"2018","unstructured":"McInnes, L., Healy, J., Saul, N., Gro\u00dfberger, L.: UMAP: uniform manifold approximation and projection. J. Open Source Softw. 3, 861 (2018)","journal-title":"J. Open Source Softw."},{"key":"1_CR26","unstructured":"Galkin, M., Denis, E., Wu, J., Hamilton, W.L.: Nodepiece: compositional and parameter-efficient representations of large knowledge graphs. Presented at the International Conference on Learning Representations (2022)"},{"key":"1_CR27","unstructured":"Gilmer, J., Schoenholz, S.S., Riley, P.F., Vinyals, O., Dahl, G.E.: Neural message passing for quantum chemistry. In: Proceedings of the 34th International Conference on Machine Learning, pp. 1263\u20131272. PMLR (2017)"},{"key":"1_CR28","unstructured":"Ying, R., Bourgeois, D., You, J., Zitnik, M., Leskovec, J.: GNNExplainer: generating explanations for graph neural networks. In: Proceedings of the 33rd International Conference on Neural Information Processing Systems, pp. 9244\u20139255. Curran Associates Inc., Red Hook (2019)"},{"key":"1_CR29","unstructured":"Veli\u010dkovi\u0107, P., Cucurull, G., Casanova, A., Romero, A., Li\u00f2, P., Bengio, Y.: Graph attention networks. Presented at the International Conference on Learning Representations, 15 February 2018"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-95838-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T11:14:22Z","timestamp":1750590862000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-95838-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031958373","9783031958380"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-95838-0_1","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"23 June 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIME","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Intelligence in Medicine","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pavia","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aime2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/aime25.aimedicine.info\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}