Abstract:
BACKGROUND:Using electronic health records data to predict events and onset of diseases is increasingly common. Relatively little is known, although, about the tradeoffs between data requirements and model utility. METHODS AND RESULTS:We examined the performance of machine learning models trained to detect prediagnostic heart failure in primary care patients using longitudinal electronic health records data. Model performance was assessed in relation to data requirements defined by the prediction window length (time before clinical diagnosis), the observation window length (duration of observation before prediction window), the number of different data domains (data diversity), the number of patient records in the training data set (data quantity), and the density of patient encounters (data density). A total of 1684 incident heart failure cases and 13 525 sex, age-category, and clinic matched controls were used for modeling. Model performance improved as (1) the prediction window length decreases, especially when <2 years; (2) the observation window length increases but then levels off after 2 years; (3) the training data set size increases but then levels off after 4000 patients; (4) more diverse data types are used, but, in order, the combination of diagnosis, medication order, and hospitalization data was most important; and (5) data were confined to patients who had ≥10 phone or face-to-face encounters in 2 years. CONCLUSIONS:These empirical findings suggest possible guidelines for the minimum amount and type of data needed to train effective disease onset predictive models using longitudinal electronic health records data.
journal_name
Circ Cardiovasc Qual Outcomesjournal_title
Circulation. Cardiovascular quality and outcomesauthors
Ng K,Steinhubl SR,deFilippi C,Dey S,Stewart WFdoi
10.1161/CIRCOUTCOMES.116.002797subject
Has Abstractpub_date
2016-11-01 00:00:00pages
649-658issue
6eissn
1941-7713issn
1941-7705pii
CIRCOUTCOMES.116.002797journal_volume
9pub_type
杂志文章abstract::Background Guidelines recommend against the use of intravenous tPA (tissue-type plasminogen activator; IV tPA) in acute ischemic stroke patients with prior ischemic stroke within 3 months. However, there are limited data on the safety of IV tPA in this population. Methods and Results A retrospective observational stud...
journal_title:Circulation. Cardiovascular quality and outcomes
pub_type: 杂志文章
doi:10.1161/CIRCOUTCOMES.119.006031
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pub_type: 杂志文章,评审
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更新日期:2010-11-01 00:00:00
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journal_title:Circulation. Cardiovascular quality and outcomes
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journal_title:Circulation. Cardiovascular quality and outcomes
pub_type: 杂志文章,多中心研究
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pub_type: 杂志文章,多中心研究,随机对照试验
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pub_type: 杂志文章,多中心研究,随机对照试验
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journal_title:Circulation. Cardiovascular quality and outcomes
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journal_title:Circulation. Cardiovascular quality and outcomes
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更新日期:2020-02-01 00:00:00
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pub_type: 杂志文章
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