M. Frize, Jeff Gilchrist, Hasmik Martirosyan, E. Bariciak
{"title":"结果评估与临床决策支持系统的整合:在新生儿重症监护病房(NICU)的应用","authors":"M. Frize, Jeff Gilchrist, Hasmik Martirosyan, E. Bariciak","doi":"10.1109/MeMeA.2015.7145194","DOIUrl":null,"url":null,"abstract":"Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim to help them make joint decisions with physicians on the direction of care for their infant. New work developed the ANN-Builder which uses an open-source artificial neural network library that would enable handling real-time data streaming and automate the process of providing risk estimations of mortality. Additionally, the patient data and risk estimations were successfully integrated into the PPADS tool. The mortality estimations surpass the clinical expectations. The next and final step will be to replace missing values in the data and add alarms for major changes in the risk estimations provided by the system.","PeriodicalId":277757,"journal":{"name":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Integration of outcome estimations with a clinical decision support system: Application in the neonatal intensive care unit (NICU)\",\"authors\":\"M. Frize, Jeff Gilchrist, Hasmik Martirosyan, E. Bariciak\",\"doi\":\"10.1109/MeMeA.2015.7145194\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim to help them make joint decisions with physicians on the direction of care for their infant. New work developed the ANN-Builder which uses an open-source artificial neural network library that would enable handling real-time data streaming and automate the process of providing risk estimations of mortality. Additionally, the patient data and risk estimations were successfully integrated into the PPADS tool. The mortality estimations surpass the clinical expectations. The next and final step will be to replace missing values in the data and add alarms for major changes in the risk estimations provided by the system.\",\"PeriodicalId\":277757,\"journal\":{\"name\":\"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MeMeA.2015.7145194\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA.2015.7145194","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of outcome estimations with a clinical decision support system: Application in the neonatal intensive care unit (NICU)
Our previous research led to the development of mortality risk estimations for infants in the neonatal intensive care unit (NICU) using quality archived databases. A decision support system was created with a clinician module containing relevant patient information and a variety of outcome estimations; the PPADS (Physician-Parent Decision Support) tool also contains a module for parents with the aim to help them make joint decisions with physicians on the direction of care for their infant. New work developed the ANN-Builder which uses an open-source artificial neural network library that would enable handling real-time data streaming and automate the process of providing risk estimations of mortality. Additionally, the patient data and risk estimations were successfully integrated into the PPADS tool. The mortality estimations surpass the clinical expectations. The next and final step will be to replace missing values in the data and add alarms for major changes in the risk estimations provided by the system.