{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T10:33:39Z","timestamp":1769855619744,"version":"3.49.0"},"publisher-location":"Cham","reference-count":75,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032095268","type":"print"},{"value":"9783032095275","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T00:00:00Z","timestamp":1761696000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T00:00:00Z","timestamp":1761696000000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-09527-5_18","type":"book-chapter","created":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T06:29:50Z","timestamp":1761805790000},"page":"328-348","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["HypKG: Hypergraph-Based Knowledge Graph Contextualization for\u00a0Precision Healthcare"],"prefix":"10.1007","author":[{"given":"Yuzhang","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ran","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaying","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carl","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,10,29]]},"reference":[{"issue":"1","key":"18_CR1","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1186\/s40537-023-00774-9","volume":"10","author":"B Abu-Salih","year":"2023","unstructured":"Abu-Salih, B., Al-Qurishi, M., Alweshah, M., Al-Smadi, M., Alfayez, R., Saadeh, H.: Healthcare knowledge graph construction: a systematic review of the state-of-the-art, open issues, and opportunities. J. Big Data 10(1), 81 (2023)","journal-title":"J. Big Data"},{"issue":"1","key":"18_CR2","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.cell.2019.02.039","volume":"177","author":"NS Abul-Husn","year":"2019","unstructured":"Abul-Husn, N.S., Kenny, E.E.: Personalized medicine and the power of electronic health records. Cell 177(1), 58\u201369 (2019)","journal-title":"Cell"},{"key":"18_CR3","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.jcot.2020.08.020","volume":"13","author":"KM Amer","year":"2021","unstructured":"Amer, K.M., Congiusta, D.V., Suri, P., Choudhry, A., Otero, K., Adams, M.: Clavicle fractures: associated trauma and morbidity. J. Clin. Orthopaedics Trauma 13, 53\u201356 (2021)","journal-title":"J. Clin. Orthopaedics Trauma"},{"issue":"3","key":"18_CR4","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1136\/jamia.2009.002733","volume":"17","author":"AR Aronson","year":"2010","unstructured":"Aronson, A.R., Lang, F.M.: An overview of metamap: historical perspective and recent advances. J. Am. Med. Inform. Assoc. 17(3), 229\u2013236 (2010)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Bhasuran, B., et al.: Preliminary analysis of the impact of lab results on large language model generated differential diagnoses. NPJ Digit. Med. 8(1), 166 (2025)","DOI":"10.1038\/s41746-025-01556-8"},{"key":"18_CR6","doi-asserted-by":"crossref","unstructured":"Bodenreider, O.: The unified medical language system (UMLS): integrating biomedical terminology. Nucl. Acids Res. 32(suppl_1), D267\u2013D270 (2004)","DOI":"10.1093\/nar\/gkh061"},{"key":"18_CR7","doi-asserted-by":"crossref","unstructured":"Bordes, A., Weston, J., Collobert, R., Bengio, Y.: Learning structured embeddings of knowledge bases. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a025, pp. 301\u2013306 (2011)","DOI":"10.1609\/aaai.v25i1.7917"},{"issue":"6","key":"18_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3643806","volume":"56","author":"J Cao","year":"2024","unstructured":"Cao, J., Fang, J., Meng, Z., Liang, S.: Knowledge graph embedding: a survey from the perspective of representation spaces. ACM Comput. Surv. 56(6), 1\u201342 (2024)","journal-title":"ACM Comput. Surv."},{"issue":"1","key":"18_CR9","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1186\/s12911-022-02070-7","volume":"23","author":"RM Carvalho","year":"2023","unstructured":"Carvalho, R.M., Oliveira, D., Pesquita, C.: Knowledge graph embeddings for ICU readmission prediction. BMC Med. Inform. Decis. Mak. 23(1), 12 (2023)","journal-title":"BMC Med. Inform. Decis. Mak."},{"key":"18_CR10","unstructured":"Chien, E., Pan, C., Peng, J., Milenkovic, O.: You are allset: a multiset function framework for hypergraph neural networks. arXiv preprint arXiv:2106.13264 (2021)"},{"key":"18_CR11","first-page":"41","volume":"2016","author":"Y Choi","year":"2016","unstructured":"Choi, Y., Chiu, C.Y.I., Sontag, D.: Learning low-dimensional representations of medical concepts. AMIA Summits Transl. Sci. Proc. 2016, 41 (2016)","journal-title":"AMIA Summits Transl. Sci. Proc."},{"issue":"1","key":"18_CR12","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1016\/j.berh.2015.04.024","volume":"29","author":"DJ Clauw","year":"2015","unstructured":"Clauw, D.J.: Diagnosing and treating chronic musculoskeletal pain based on the underlying mechanism (s). Best Pract. Res. Clin. Rheumatol. 29(1), 6\u201319 (2015)","journal-title":"Best Pract. Res. Clin. Rheumatol."},{"key":"18_CR13","doi-asserted-by":"crossref","unstructured":"Cui, H., et al.: A review on knowledge graphs for healthcare: resources, applications, and promises. J. Biomed. Inf. 104861 (2025)","DOI":"10.1016\/j.jbi.2025.104861"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Dalal, P., Shah, G., Chhabra, D., Gallon, L.: Role of tacrolimus combination therapy with mycophenolate mofetil in the prevention of organ rejection in kidney transplant patients. Int. J. Nephrol. Renovascular Diseas. 107\u2013115 (2010)","DOI":"10.2147\/IJNRD.S7044"},{"issue":"21","key":"18_CR15","doi-asserted-by":"publisher","first-page":"2286","DOI":"10.1001\/jama.2012.5034","volume":"307","author":"G De Berardis","year":"2012","unstructured":"De Berardis, G., et al.: Association of aspirin use with major bleeding in patients with and without diabetes. JAMA 307(21), 2286\u20132294 (2012)","journal-title":"JAMA"},{"key":"18_CR16","doi-asserted-by":"crossref","unstructured":"D\u2019Souza, J., Ng, V.: Sieve-based entity linking for the biomedical domain. In: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 297\u2013302 (2015)","DOI":"10.3115\/v1\/P15-2049"},{"issue":"6","key":"18_CR17","first-page":"571","volume":"140","author":"PG Gallagher","year":"2022","unstructured":"Gallagher, P.G.: Anemia in the pediatric patient. Blood J. the Am. Soc. Hematol. 140(6), 571\u2013593 (2022)","journal-title":"Blood J. the Am. Soc. Hematol."},{"key":"18_CR18","unstructured":"Gao, Y., et al.: Leveraging a medical knowledge graph into large language models for diagnosis prediction. arXiv preprint arXiv:2308.14321 (2023)"},{"issue":"19","key":"18_CR19","doi-asserted-by":"publisher","first-page":"1829","DOI":"10.1016\/j.jacc.2007.11.080","volume":"51","author":"AY Gasparyan","year":"2008","unstructured":"Gasparyan, A.Y., Watson, T., Lip, G.Y.: The role of aspirin in cardiovascular prevention: implications of aspirin resistance. J. Am. Coll. Cardiol. 51(19), 1829\u20131843 (2008)","journal-title":"J. Am. Coll. Cardiol."},{"key":"18_CR20","doi-asserted-by":"crossref","unstructured":"German Advisory Committee Blood (Arbeitskreis\u00a0Blut), S.A.o.P.T.b.B.: Human immunodeficiency virus (HIV). Transf. Med. Hemotherapy 43(3), 203\u2013222 (2016)","DOI":"10.1159\/000445852"},{"key":"18_CR21","doi-asserted-by":"crossref","unstructured":"Hulens, M., Rasschaert, R., Vansant, G., Stalmans, I., Bruyninckx, F., Dankaerts, W.: The link between idiopathic intracranial hypertension, fibromyalgia, and chronic fatigue syndrome: exploration of a shared pathophysiology. J. Pain Res. 3129\u20133140 (2018)","DOI":"10.2147\/JPR.S186878"},{"key":"18_CR22","first-page":"269","volume":"2020","author":"Z Ji","year":"2020","unstructured":"Ji, Z., Wei, Q., Xu, H.: Bert-based ranking for biomedical entity normalization. AMIA Summits Transl. Sci. Proc. 2020, 269 (2020)","journal-title":"AMIA Summits Transl. Sci. Proc."},{"key":"18_CR23","unstructured":"Jiang, P., Xiao, C., Cross, A.R., Sun, J.: Graphcare: enhancing healthcare predictions with personalized knowledge graphs. In: The Twelfth International Conference on Learning Representations (2024)"},{"issue":"1","key":"18_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/sdata.2016.35","volume":"3","author":"AE Johnson","year":"2016","unstructured":"Johnson, A.E., et al.: Mimic-III, a freely accessible critical care database. Sci. Data 3(1), 1\u20139 (2016)","journal-title":"Sci. Data"},{"key":"18_CR25","doi-asserted-by":"crossref","unstructured":"Johnson, R., Li, M.M., Noori, A., Queen, O., Zitnik, M.: Graph artificial intelligence in medicine. Ann. Rev. Biomed. Data Sci. 7 (2024)","DOI":"10.1146\/annurev-biodatasci-110723-024625"},{"issue":"5","key":"18_CR26","doi-asserted-by":"publisher","first-page":"848","DOI":"10.1016\/j.pcd.2021.05.010","volume":"15","author":"M Jo\u0144ca","year":"2021","unstructured":"Jo\u0144ca, M., Kr\u00f3tki, F., Tomasik, P.: The effect of disinfecting procedure on the glucose concentration using a personal glucose meter. Prim. Care Diabetes 15(5), 848\u2013852 (2021)","journal-title":"Prim. Care Diabetes"},{"issue":"4","key":"18_CR27","doi-asserted-by":"publisher","first-page":"161","DOI":"10.3390\/info13040161","volume":"13","author":"M Kejriwal","year":"2022","unstructured":"Kejriwal, M.: Knowledge graphs: a practical review of the research landscape. Information 13(4), 161 (2022)","journal-title":"Information"},{"issue":"3","key":"18_CR28","doi-asserted-by":"publisher","DOI":"10.2196\/22219","volume":"23","author":"IS Kohane","year":"2021","unstructured":"Kohane, I.S., et al.: What every reader should know about studies using electronic health record data but may be afraid to ask. J. Med. Internet Res. 23(3), e22219 (2021)","journal-title":"J. Med. Internet Res."},{"issue":"1","key":"18_CR29","volume":"2012","author":"Z Kurugol","year":"2012","unstructured":"Kurugol, Z., Onen, S.S., Koturoglu, G.: Severe hemolytic anemia associated with mild pneumonia caused by mycoplasma pneumonia. Case Rep. Med. 2012(1), 649850 (2012)","journal-title":"Case Rep. Med."},{"key":"18_CR30","doi-asserted-by":"crossref","unstructured":"Lee, G., Bu, F., Eliassi-Rad, T., Shin, K.: A survey on hypergraph mining: patterns, tools, and generators. arXiv preprint arXiv:2401.08878 (2024)","DOI":"10.1145\/3719002"},{"key":"18_CR31","unstructured":"Lee, J., Lee, Y., Kim, J., Kosiorek, A., Choi, S., Teh, Y.W.: Set transformer: a framework for attention-based permutation-invariant neural networks. In: International conference on machine learning. pp. 3744\u20133753. PMLR (2019)"},{"key":"18_CR32","doi-asserted-by":"crossref","unstructured":"Liu, F., Shareghi, E., Meng, Z., Basaldella, M., Collier, N.: Self-alignment pretraining for biomedical entity representations. arXiv preprint arXiv:2010.11784 (2020)","DOI":"10.18653\/v1\/2021.naacl-main.334"},{"key":"18_CR33","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wang, X., Wang, B., Huang, Z., Yang, C., Jin, W.: Graph odes and beyond: a comprehensive survey on integrating differential equations with graph neural networks. arXiv preprint arXiv:2503.23167 (2025)","DOI":"10.1145\/3711896.3736559"},{"key":"18_CR34","doi-asserted-by":"crossref","unstructured":"Lu, J., Shen, J., Xiong, B., Ma, W., Staab, S., Yang, C.: HiproMPT: few-shot biomedical knowledge fusion via hierarchy-oriented prompting. In: 46th International ACM SIGIR Conference on Research and Development in Information Retrieval - Short Paper (2023)","DOI":"10.1145\/3539618.3591997"},{"issue":"2","key":"18_CR35","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1111\/head.12769","volume":"56","author":"S Lucas","year":"2016","unstructured":"Lucas, S.: The pharmacology of indomethacin. Headache J. Head Face Pain 56(2), 436\u2013446 (2016)","journal-title":"Headache J. Head Face Pain"},{"issue":"10","key":"18_CR36","doi-asserted-by":"publisher","first-page":"e158","DOI":"10.2337\/dc15-1096","volume":"38","author":"DM Maahs","year":"2015","unstructured":"Maahs, D.M., et al.: Effect of acetaminophen on CGM glucose in an outpatient setting. Diabetes Care 38(10), e158\u2013e159 (2015)","journal-title":"Diabetes Care"},{"key":"18_CR37","doi-asserted-by":"crossref","unstructured":"Manikandan, R., Kuwelkar, S., Sivakumar, R.: An hybrid technique for optimized clustering of EHR using binary particle swarm and constrained optimization for better performance in prediction of cardiovascular diseases. Measur. Sens. 25, 100577 (2023)","DOI":"10.1016\/j.measen.2022.100577"},{"key":"18_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2023.104403","volume":"143","author":"L Murali","year":"2023","unstructured":"Murali, L., Gopakumar, G., Viswanathan, D.M., Nedungadi, P.: Towards electronic health record-based medical knowledge graph construction, completion, and applications: a literature study. J. Biomed. Inform. 143, 104403 (2023)","journal-title":"J. Biomed. Inform."},{"issue":"4","key":"18_CR39","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1148\/rg.2021200154","volume":"41","author":"M Naeem","year":"2021","unstructured":"Naeem, M., et al.: Imaging manifestations of genitourinary tuberculosis. Radiographics 41(4), 1123\u20131143 (2021)","journal-title":"Radiographics"},{"issue":"6","key":"18_CR40","first-page":"524","volume":"27","author":"K Novick","year":"2022","unstructured":"Novick, K., Cober, M.P.: Evaluation of inpatient starter parenteral nutrition use in the neonatal intensive care unit. J. Pediat. Pharmacol. Therapeut. 27(6), 524\u2013528 (2022)","journal-title":"J. Pediat. Pharmacol. Therapeut."},{"key":"18_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2022.102359","volume":"131","author":"JGD Ochoa","year":"2022","unstructured":"Ochoa, J.G.D., Mustafa, F.E.: Graph neural network modelling as a potentially effective method for predicting and analyzing procedures based on patients\u2019 diagnoses. Artif. Intell. Med. 131, 102359 (2022)","journal-title":"Artif. Intell. Med."},{"issue":"2","key":"18_CR42","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1089\/aid.2011.0275","volume":"29","author":"J Reynes","year":"2013","unstructured":"Reynes, J., et al.: Lopinavir\/ritonavir combined with raltegravir or tenofovir\/emtricitabine in antiretroviral-naive subjects: 96-week results of the progress study. AIDS Res. Hum. Retroviruses 29(2), 256\u2013265 (2013)","journal-title":"AIDS Res. Hum. Retroviruses"},{"issue":"3","key":"18_CR43","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1001\/jama.291.3.325","volume":"291","author":"MH Samore","year":"2004","unstructured":"Samore, M.H., et al.: Surveillance of medical device-related hazards and adverse events in hospitalized patients. JAMA 291(3), 325\u2013334 (2004)","journal-title":"JAMA"},{"key":"18_CR44","doi-asserted-by":"crossref","unstructured":"Sch\u00fcssler, S.C., et al.: Seizures in preterm infants with germinal-matrix-intraventricular hemorrhage (GM-IVH): a retrospective monocentric study on predictors and neurodevelopmental outcome. Eur. J. Paediatr. Neurol. (2025)","DOI":"10.1016\/j.ejpn.2025.04.012"},{"issue":"3","key":"18_CR45","doi-asserted-by":"publisher","first-page":"130","DOI":"10.5492\/wjccm.v12.i3.130","volume":"12","author":"O Singh","year":"2023","unstructured":"Singh, O., Juneja, D.: Upper extremity deep vein thrombosis: an intensivist\u2019s perspective. World J. Crit. Care Med. 12(3), 130 (2023)","journal-title":"World J. Crit. Care Med."},{"issue":"7972","key":"18_CR46","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1038\/s41586-023-06291-2","volume":"620","author":"K Singhal","year":"2023","unstructured":"Singhal, K., et al.: Large language models encode clinical knowledge. Nature 620(7972), 172\u2013180 (2023)","journal-title":"Nature"},{"key":"18_CR47","doi-asserted-by":"crossref","unstructured":"Speer, R., Chin, J., Havasi, C.: Conceptnet 5.5: an open multilingual graph of general knowledge. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a031 (2017)","DOI":"10.1609\/aaai.v31i1.11164"},{"key":"18_CR48","doi-asserted-by":"crossref","unstructured":"Su, C., et\u00a0al.: Biomedical discovery through the integrative biomedical knowledge hub (IBKH). Iscience 26(4) (2023)","DOI":"10.1016\/j.isci.2023.106460"},{"key":"18_CR49","doi-asserted-by":"crossref","unstructured":"Sun, W., Cai, Z., Li, Y., Liu, F., Fang, S., Wang, G.: Data processing and text mining technologies on electronic medical records: a review. J. Healthcare Eng. 2018 (2018)","DOI":"10.1155\/2018\/4302425"},{"key":"18_CR50","doi-asserted-by":"crossref","unstructured":"Theodoropoulos, C., Mulligan, N., Stappenbeck, T., Bettencourt-Silva, J.: Representation learning for person or entity-centric knowledge graphs: an application in healthcare. In: Proceedings of the 12th Knowledge Capture Conference 2023, pp. 225\u2013233 (2023)","DOI":"10.1145\/3587259.3627545"},{"key":"18_CR51","unstructured":"Trouillon, T., Welbl, J., Riedel, S., Gaussier, \u00c9., Bouchard, G.: Complex embeddings for simple link prediction. In: International Conference on Machine Learning, pp. 2071\u20132080. PMLR (2016)"},{"key":"18_CR52","unstructured":"Vashishth, S., Sanyal, S., Nitin, V., Talukdar, P.: Composition-based multi-relational graph convolutional networks. In: International Conference on Learning Representations"},{"issue":"8","key":"18_CR53","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1089\/cmb.2017.0023","volume":"24","author":"I Vasiljeva","year":"2017","unstructured":"Vasiljeva, I., Arandjelovi\u0107, O.: Diagnosis prediction from electronic health records using the binary diagnosis history vector representation. J. Comput. Biol. 24(8), 767\u2013786 (2017)","journal-title":"J. Comput. Biol."},{"issue":"2","key":"18_CR54","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1093\/ajhp\/55.2.154","volume":"55","author":"SE Walker","year":"1998","unstructured":"Walker, S.E., Gray, S., Schmidt, B.: Stability of reconstituted indomethacin sodium trihydrate in original vials and polypropylene syringes. Am. J. Health Syst. Pharm. 55(2), 154\u2013158 (1998)","journal-title":"Am. J. Health Syst. Pharm."},{"issue":"3","key":"18_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3611651","volume":"56","author":"B Wang","year":"2023","unstructured":"Wang, B., et al.: Pre-trained language models in biomedical domain: a systematic survey. ACM Comput. Surv. 56(3), 1\u201352 (2023)","journal-title":"ACM Comput. Surv."},{"issue":"4","key":"18_CR56","doi-asserted-by":"publisher","first-page":"1054","DOI":"10.1161\/STROKEAHA.121.035850","volume":"53","author":"AJ Webb","year":"2022","unstructured":"Webb, A.J., Werring, D.J.: New insights into cerebrovascular pathophysiology and hypertension. Stroke 53(4), 1054\u20131064 (2022)","journal-title":"Stroke"},{"issue":"7","key":"18_CR57","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0255192","volume":"16","author":"J Wolff","year":"2021","unstructured":"Wolff, J., et al.: Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders. PLoS ONE 16(7), e0255192 (2021)","journal-title":"PLoS ONE"},{"issue":"6","key":"18_CR58","doi-asserted-by":"publisher","first-page":"S106","DOI":"10.1097\/MLR.0b013e3181de9e17","volume":"48","author":"J Wu","year":"2010","unstructured":"Wu, J., Roy, J., Stewart, W.F.: Prediction modeling using EHR data: challenges, strategies, and a comparison of machine learning approaches. Med. Care 48(6), S106\u2013S113 (2010)","journal-title":"Med. Care"},{"key":"18_CR59","doi-asserted-by":"crossref","unstructured":"Wu, Y., et al.: Prediction of post-stroke AF in ESUS patients is enhanced by combining expert-derived predictors and embedding of full diagnostic codes using pre-trained hypergraph neural networks. In: STROKE. vol.\u00a056. Lippincott Williams & Wilkins Two Commerce SQ, 2001 Market ST, Philadelphia\u00a0$$\\ldots $$ (2025)","DOI":"10.1161\/str.56.suppl_1.TMP102"},{"key":"18_CR60","unstructured":"Xie, Y., et al.: KERAP: a knowledge-enhanced reasoning approach for accurate zero-shot diagnosis prediction using multi-agent LLMs. arXiv preprint arXiv:2507.02773 (2025)"},{"key":"18_CR61","doi-asserted-by":"crossref","unstructured":"Xie, Y., Lu, J., Ho, J., Nahab, F., Hu, X., Yang, C.: Promptlink: leveraging large language models for cross-source biomedical concept linking. In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 2589\u20132593 (2024)","DOI":"10.1145\/3626772.3657904"},{"key":"18_CR62","doi-asserted-by":"crossref","unstructured":"Xie, Y., et al.: Abstract wp175: predicting post-stroke cognitive impairment (PSCI) using multiple machine learning approaches. Stroke 56(Suppl_1), AWP175\u2013AWP175 (2025)","DOI":"10.1161\/str.56.suppl_1.WP175"},{"key":"18_CR63","doi-asserted-by":"crossref","unstructured":"Xie, Y., Niu, G., Da, Q., Dai, W., Yang, Y.: Survival prediction for gastric cancer via multimodal learning of whole slide images and gene expression. In: 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1311\u20131316. IEEE (2022)","DOI":"10.1109\/BIBM55620.2022.9995480"},{"key":"18_CR64","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2024.102871","volume":"152","author":"Y Xie","year":"2024","unstructured":"Xie, Y., et al.: Improving diagnosis and outcome prediction of gastric cancer via multimodal learning using whole slide pathological images and gene expression. Artif. Intell. Med. 152, 102871 (2024)","journal-title":"Artif. Intell. Med."},{"key":"18_CR65","doi-asserted-by":"crossref","unstructured":"Xu, D., Zhang, Z., Bethard, S.: A generate-and-rank framework with semantic type regularization for biomedical concept normalization. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 8452\u20138464 (2020)","DOI":"10.18653\/v1\/2020.acl-main.748"},{"key":"18_CR66","first-page":"582","volume":"2023","author":"R Xu","year":"2023","unstructured":"Xu, R., Ali, M.K., Ho, J.C., Yang, C.: Hypergraph transformers for EHR-based clinical predictions. AMIA Summits Transl. Sci. Proc. 2023, 582 (2023)","journal-title":"AMIA Summits Transl. Sci. Proc."},{"key":"18_CR67","unstructured":"Xu, R., Yu, Y., Zhang, C., Ali, M.K., Ho, J.C., Yang, C.: Counterfactual and factual reasoning over hypergraphs for interpretable clinical predictions on EHR. In: Machine Learning for Health, pp. 259\u2013278. PMLR (2022)"},{"key":"18_CR68","doi-asserted-by":"crossref","unstructured":"Xu, Y., et al.: Seqcare: sequential training with external medical knowledge graph for diagnosis prediction in healthcare data. In: Proceedings of the ACM Web Conference 2023, pp. 2819\u20132830 (2023)","DOI":"10.1145\/3543507.3583543"},{"key":"18_CR69","first-page":"8374","volume":"35","author":"H Yang","year":"2022","unstructured":"Yang, H., Lin, Z., Zhang, M.: Rethinking knowledge graph evaluation under the open-world assumption. Adv. Neural. Inf. Process. Syst. 35, 8374\u20138385 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"18_CR70","doi-asserted-by":"crossref","unstructured":"Yang, Y., Huang, C., Xia, L., Li, C.: Knowledge graph contrastive learning for recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1434\u20131443 (2022)","DOI":"10.1145\/3477495.3532009"},{"key":"18_CR71","doi-asserted-by":"crossref","unstructured":"Ye, M., Cui, S., Wang, Y., Luo, J., Xiao, C., Ma, F.: Medpath: augmenting health risk prediction via medical knowledge paths. In: Proceedings of the Web Conference 2021, pp. 1397\u20131409 (2021)","DOI":"10.1145\/3442381.3449860"},{"key":"18_CR72","doi-asserted-by":"crossref","unstructured":"Yu, Y., Zuo, S., Jiang, H., Ren, W., Zhao, T., Zhang, C.: Fine-tuning pre-trained language model with weak supervision: a contrastive-regularized self-training approach. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 1063\u20131077 (2021)","DOI":"10.18653\/v1\/2021.naacl-main.84"},{"key":"18_CR73","doi-asserted-by":"crossref","unstructured":"Zhang, S., et al.: Knowledge-rich self-supervision for biomedical entity linking. In: Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 868\u2013880 (2022)","DOI":"10.18653\/v1\/2022.findings-emnlp.61"},{"issue":"6","key":"18_CR74","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2020.102324","volume":"57","author":"Y Zhang","year":"2020","unstructured":"Zhang, Y., et al.: HKGB: an inclusive, extensible, intelligent, semi-auto-constructed knowledge graph framework for healthcare with clinicians\u2019 expertise incorporated. Inf. Process. Manag. 57(6), 102324 (2020)","journal-title":"Inf. Process. Manag."},{"key":"18_CR75","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Cui, H., Xu, R., Xie, Y., Ho, J.C., Yang, C.: TACCO: task-guided co-clustering of clinical concepts and patient visits for disease subtyping based on EHR data. In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 6324\u20136334 (2024)","DOI":"10.1145\/3637528.3671594"}],"container-title":["Lecture Notes in Computer Science","The Semantic Web \u2013 ISWC 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-09527-5_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T06:30:20Z","timestamp":1761805820000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-09527-5_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,29]]},"ISBN":["9783032095268","9783032095275"],"references-count":75,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-09527-5_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,29]]},"assertion":[{"value":"29 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISWC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Semantic Web Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nara","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Japan","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":"2 November 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 November 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"semweb2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iswc2025.semanticweb.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}