{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,8]],"date-time":"2026-02-08T11:33:26Z","timestamp":1770550406405,"version":"3.49.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,7]],"date-time":"2022-08-07T00:00:00Z","timestamp":1659830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"National Institute of Health","award":["P20GM103499"],"award-info":[{"award-number":["P20GM103499"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,7]]},"DOI":"10.1145\/3535508.3545513","type":"proceedings-article","created":{"date-parts":[[2022,7,28]],"date-time":"2022-07-28T22:26:03Z","timestamp":1659047163000},"page":"1-4","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Application of machine learning for patient response prediction to cardiac resynchronization therapy"],"prefix":"10.1145","author":[{"given":"Brendan E.","family":"Odigwe","sequence":"first","affiliation":[{"name":"U. of South Carolina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alireza Bagheri","family":"Rajeoni","sequence":"additional","affiliation":[{"name":"U. of South Carolina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Celestine I.","family":"Odigwe","sequence":"additional","affiliation":[{"name":"Thomas Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francis G.","family":"Spinale","sequence":"additional","affiliation":[{"name":"U. of South Carolina"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Homayoun","family":"Valafar","sequence":"additional","affiliation":[{"name":"U. of South Carolina"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,7]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"https:\/\/healthitanalytics.com\/features\/how-machine-learning-is-transforming-clinical-decision-support-tools (accessed","year":"2020","unstructured":"\"How Machine Learning is Transforming Clinical Decision Support Tools,\" 2020. https:\/\/healthitanalytics.com\/features\/how-machine-learning-is-transforming-clinical-decision-support-tools (accessed Nov. 06, 2020 ). \"How Machine Learning is Transforming Clinical Decision Support Tools,\" 2020. https:\/\/healthitanalytics.com\/features\/how-machine-learning-is-transforming-clinical-decision-support-tools (accessed Nov. 06, 2020)."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/45.84097"},{"key":"e_1_3_2_1_3_1","unstructured":"IEEE Journals & Magazine.\" https:\/\/ieeexplore.ieee.org\/document\/84097 (accessed 2020 Artificial neural networks -"},{"key":"e_1_3_2_1_4_1","volume-title":"Accessed","author":"Wu S.","year":"2020","unstructured":"S. Wu , W. Zhang , F. Sun , and B. Cui , \" Graph Neural Networks in Recommender Systems: A Survey,\" Nov. 2020 , Accessed : Nov. 11, 2020 . [Online]. Available : http:\/\/arxiv.org\/abs\/2011.02260. S. Wu, W. Zhang, F. Sun, and B. Cui, \"Graph Neural Networks in Recommender Systems: A Survey,\" Nov. 2020, Accessed: Nov. 11, 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/2011.02260."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.2105.08907"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/CSCI49370.2019.00171"},{"key":"e_1_3_2_1_7_1","first-page":"584","volume-title":"Conf. Comput. Sci. Comput. Intell. CSCI 2019","author":"Zhao L.","year":"2019","unstructured":"L. Zhao , B. Odigwe , S. Lessner , D. G. Clair , F. Mussa , and H. Valafar , \" Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques,\" Proc. - 6th Annu . Conf. Comput. Sci. Comput. Intell. CSCI 2019 , pp. 584 -- 589 , Dec. 2019 , Accessed : Nov. 11, 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/1912.06010. L. Zhao, B. Odigwe, S. Lessner, D. G. Clair, F. Mussa, and H. Valafar, \"Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques,\" Proc. - 6th Annu. Conf. Comput. Sci. Comput. Intell. CSCI 2019, pp. 584--589, Dec. 2019, Accessed: Nov. 11, 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/1912.06010."},{"key":"e_1_3_2_1_8_1","unstructured":"A. B. Rajeoni \"ANALOG CIRCUIT SIZING USING MACHINE LEARNING BASED TRANSISTOR \" 2021.  A. B. Rajeoni \"ANALOG CIRCUIT SIZING USING MACHINE LEARNING BASED TRANSISTOR \" 2021."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40537-019-0225-0"},{"key":"e_1_3_2_1_10_1","volume-title":"Accessed","author":"Odigwe B. E.","year":"2020","unstructured":"B. E. Odigwe , J. S. Eyitayo , C. I. Odigwe , and H. Valafar , \" Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks,\" Nov. 2019 , Accessed : May 26, 2020 . [Online]. Available : http:\/\/arxiv.org\/abs\/1911.10978. B. E. Odigwe, J. S. Eyitayo, C. I. Odigwe, and H. Valafar, \"Modelling of Sickle Cell Anemia Patients Response to Hydroxyurea using Artificial Neural Networks,\" Nov. 2019, Accessed: May 26, 2020. [Online]. Available: http:\/\/arxiv.org\/abs\/1911.10978."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa032423"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa050496"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacc.2008.11.013"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.110.992552"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.110.014324"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ahj.2005.06.024"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.hrthm.2018.11.026"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCRESAHA.113.300268"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1540-8159.2009.02581.x"},{"key":"e_1_3_2_1_20_1","volume-title":"Economic Value and Cost-Effectiveness of Cardiac Resynchronization Therapy Among Patients With Mild Heart Failure Projections From the REVERSE Long-Term Follow-Up","author":"Gold M. R.","year":"2017","unstructured":"M. R. Gold , A. Padhiar , S. Mealing , M. K. Sidhu , S. I. Tsintzos , and W. T. Abraham , \" Economic Value and Cost-Effectiveness of Cardiac Resynchronization Therapy Among Patients With Mild Heart Failure Projections From the REVERSE Long-Term Follow-Up ,\" 2017 . M. R. Gold, A. Padhiar, S. Mealing, M. K. Sidhu, S. I. Tsintzos, and W. T. Abraham, \"Economic Value and Cost-Effectiveness of Cardiac Resynchronization Therapy Among Patients With Mild Heart Failure Projections From the REVERSE Long-Term Follow-Up,\" 2017."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1093\/europace\/eur079"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.48550\/arxiv.2109.06139"}],"event":{"name":"BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","location":"Northbrook Illinois","acronym":"BCB '22","sponsor":["SIGBIOM ACM Special Interest Group on Biomedical Computing"]},"container-title":["Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3535508.3545513","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3535508.3545513","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T17:49:47Z","timestamp":1750268987000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3535508.3545513"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,7]]},"references-count":22,"alternative-id":["10.1145\/3535508.3545513","10.1145\/3535508"],"URL":"https:\/\/doi.org\/10.1145\/3535508.3545513","relation":{},"subject":[],"published":{"date-parts":[[2022,8,7]]},"assertion":[{"value":"2022-08-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}