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Causal discovery from time series data

2022-07-01Master thesis Open access
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dc.contributor.advisorCoelho, Luís
dc.contributor.advisorFraunhofer, Vitor Rolla
dc.contributor.advisorFraunhofer, Vânia Guimarães
dc.contributor.authorAlmeida, Fernanda Ribeiro de
dc.date.accessioned2023-01-17T09:57:01Z
dc.date.available2023-01-17T09:57:01Z
dc.date.issued2022-07-01
dc.description.abstractThe drive to understand the laws that govern the universe and ourselves in order to expand our view of reality is deeply rooted in humanity. In science, this urge is a robust process filled with challenges and opportunities given the rapidly growing technology-driven volume of time series data. Causal discovery supports science in an innovative and fast-growing manner with the essential goal of uncovering mathematical orders directly from observational data translated into causal association networks. This scientific tool pledges to accelerate growth in various fields, including life sciences. This work approaches the topic of causal discovery on two levels. First, we address the theory of constraint-based methods on detecting and quantifying causal relations, covering how the methods work, the challenges they face, and the opportunities they present. Second, we explore the PCMCI method with an implementation on both synthetic and real-world data. The results of this work found in applying causal discovery in real physiological signals data may provide insights into the prospects and difficulties of causal structure search in healthcare Big Data and, moreover, the advantages of using causal models in prediction.pt_PT
dc.identifier.tid203147472pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/21571
dc.language.isoengpt_PT
dc.subjectCausal discoverypt_PT
dc.subjectCausal relationspt_PT
dc.subjectTime-series datapt_PT
dc.subjectPhysiological signalspt_PT
dc.subjectMIMIC IIIpt_PT
dc.titleCausal discovery from time series datapt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameTecnologia Médica e Negócios em Saúdept_PT

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