Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Journal: Digestive diseases and sciences

PMID: 26537487

Abstract

BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computational identification methods. The present study sought to design a classification algorithm for NAFLD within the electronic medical record (EMR) for the development of large-scale longitudinal cohorts.

Authors

Kathleen E Corey

Gastrointestinal Unit, Massachusetts General Hospital, 55 Fruit Street, Blake 4, Boston, MA, 02114, USA. kcorey@partners.org.
Uri Kartoun

Harvard Medical School, Boston, MA, USA.
Hui Zheng

Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China.
Stanley Y Shaw

Massachusetts General Hospital, Boston, MA.

Keywords

Adult Aged Alanine Transaminase Algorithms Aspartate Aminotransferases Biopsy Cohort Studies Data Collection Diabetes Mellitus Electronic Health Records Female Humans International Classification of Diseases Logistic Models Male Middle Aged Natural Language Processing Non-alcoholic Fatty Liver Disease Prevalence Triglycerides United States

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View on PubMed Access via DOI PubMed (26537487)

Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Abstract

Authors

Keywords

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