Analysis of irregularly sampled time series health care data sets
The real-world healthcare system generates abundant time-series data. In most cases, these data have a high prevalence of missing values and are often irregularly sampled across both time and patient. Moreover, due to the complex level of a different dataset, the preprocessing is more significant an...
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Format: | Thesis-Master by Coursework |
Language: | English |
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Nanyang Technological University
2022
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Online Access: | https://hdl.handle.net/10356/154677 |
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Institution: | Nanyang Technological University |
Language: | English |