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Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.

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Title: Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.
Authors: Sparapani RA; From the Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI., Teng BQ; From the Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI., Hilbrands J; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI., Pipkorn R; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI., Feuling MB; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI., Goday PS; the Pediatric Gastroenterology and Nutrition, Medical College of Wisconsin, Milwaukee, WI.
Source: Journal of pediatric gastroenterology and nutrition [J Pediatr Gastroenterol Nutr] 2022 Aug 01; Vol. 75 (2), pp. 210-214. Date of Electronic Publication: 2022 Jun 01.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: Wiley Country of Publication: United States NLM ID: 8211545 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-4801 (Electronic) Linking ISSN: 02772116 NLM ISO Abbreviation: J Pediatr Gastroenterol Nutr Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.
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  Data: <searchLink fieldCode="AU" term="%22Sparapani+RA%22">Sparapani RA</searchLink>; From the Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI.<br /><searchLink fieldCode="AU" term="%22Teng+BQ%22">Teng BQ</searchLink>; From the Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI.<br /><searchLink fieldCode="AU" term="%22Hilbrands+J%22">Hilbrands J</searchLink>; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI.<br /><searchLink fieldCode="AU" term="%22Pipkorn+R%22">Pipkorn R</searchLink>; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI.<br /><searchLink fieldCode="AU" term="%22Feuling+MB%22">Feuling MB</searchLink>; the Clinical Nutrition, Children's Wisconsin, Milwaukee, WI.<br /><searchLink fieldCode="AU" term="%22Goday+PS%22">Goday PS</searchLink>; the Pediatric Gastroenterology and Nutrition, Medical College of Wisconsin, Milwaukee, WI.
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  Data: <searchLink fieldCode="JN" term="%228211545%22">Journal of pediatric gastroenterology and nutrition</searchLink> [J Pediatr Gastroenterol Nutr] 2022 Aug 01; Vol. 75 (2), pp. 210-214. <i>Date of Electronic Publication: </i>2022 Jun 01.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Wiley%22">Wiley </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>8211545 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1536-4801 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2202772116%22">02772116 </searchLink><i>NLM ISO Abbreviation: </i>J Pediatr Gastroenterol Nutr <i>Subsets: </i>MEDLINE
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        Value: 10.1097/MPG.0000000000003492
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        Text: English
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      – TitleFull: Novel Pediatric Height Outlier Detection Methodology for Electronic Health Records via Machine Learning With Monotonic Bayesian Additive Regression Trees.
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              Text: 2022 Aug 01
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