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Towards Understanding ICU Procedures using Similarities in Patient Trajectories: An exploratory study on the MIMIC-III intensive care database
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
2018 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Recent advancements in Artificial Intelligence has prompted a shearexplosion of new research initiatives and applications, improving notonly existing technologies, but also opening up opportunities for newand exiting applications. This thesis explores the MIMIC-III intensive care unit database and conducts experiment on an interpretable feature space based on sever-ty scores, defining a patient health state, commonly used to predict mortality in an ICU setting. Patient health state trajectories are clustered and correlated with administered medication and performed procedures to get a better understanding of the potential usefulness in evaluating treatments on their effect on said health state, where commonalities and deviations in treatment can be understood. Furthermore, medication and procedure classification is carried out to explore their predictability using the severity subscore feature space.

sted, utgiver, år, opplag, sider
2018. , s. 124
Emneord [en]
ICU, Severity Scores, Patient Clustering, Mortality, Health State, Patient Trajectory, Clustering, Unsupervised learning, Classification, Data Mining, AI
HSV kategori
Identifikatorer
URN: urn:nbn:se:hh:diva-37416OAI: oai:DiVA.org:hh-37416DiVA, id: diva2:1229433
Fag / kurs
Computer science and engineering
Utdanningsprogram
Master's Programme in Embedded and Intelligent Systems, 120 credits
Veileder
Examiner
Tilgjengelig fra: 2018-07-02 Laget: 2018-06-29 Sist oppdatert: 2018-07-02bibliografisk kontrollert

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