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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: Apr 25, 2024
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Liver disease[original query]>>Original Studies[Product Type]
Evaluation of the Genetic Background of Patients with Niemann-Pick Disease.
Fatemeh Alipouran et al. Rep Biochem Mol Biol 2024 12(3) 386-392
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Radiomics-based prediction of nonalcoholic fatty liver disease following pancreatoduodenectomy.
Takehiro Fujii et al. Surg Today 2024
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HFE genotypes, haemochromatosis diagnosis and clinical outcomes at age 80 years: a prospective cohort study in the UK Biobank.
Mitchell R Lucas et al. BMJ Open 2024 14(3) e081926
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Risk of major adverse liver outcomes among first-degree relatives of individuals with MASLD.
Wen Yang et al. Liver Int 2024
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Combinatorial Use of Machine Learning and Logistic Regression for Predicting Carotid Plaque Risk Among 5.4 Million Adults With Fatty Liver Disease Receiving Health Check-Ups: Population-Based Cross-Sectional Study.
Yuhan Deng et al. JMIR Public Health Surveill 2023 9e47095
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Hepatic Involvement across the Metabolic Syndrome Spectrum: Non-Invasive Assessment and Risk Prediction Using Machine Learning.
Adelaida Solomon et al. J Clin Med 2023 12(17)
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Screening and clinical characteristics analysis of familial hypercholesterolemia in a tertiary public hospital.
Tianzhou Shen et al. Front Cardiovasc Med 2023 101237261
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Advancing diagnosis and management of liver disease in adults through exome sequencing.
Melanie Zheng et al. EBioMedicine 2023 95104747
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Metabolic-associated fatty liver disease and liver fibrosis scores as COVID-19 outcome predictors: a machine-learning application.
Mirko Zoncapè et al. Intern Emerg Med 2023
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Development and validation of machine learning models for nonalcoholic fatty liver disease.
Hong-Ye Peng et al. Hepatobiliary & pancreatic diseases international : HBPD INT 2023
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Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.
Timo Schulte et al. International journal of environmental research and public health 2023 20(6)
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Adverse effect of PNPLA3 p.I148M genetic variant on kidney function in middle-aged individuals with metabolic dysfunction.
Alessandro Mantovani et al. Alimentary pharmacology & therapeutics 2023
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Nonalcoholic fatty liver disease (NAFLD) detection and deep learning in a Chinese community-based population.
Yang Yang et al. European radiology 2023
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Assessment of Helicobacter pylori infection by deep learning based on endoscopic videos in real time.
Yan-Dong Li et al. Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver 2023
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Incidence of transaminitis in adults with cystic fibrosis taking elexacaftor/tezacaftor/ivacaftor.
Marci Wood et al. Journal of the American Pharmacists Association : JAPhA 2023
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Ultrasound-Based Machine Learning Approach for Detection of Nonalcoholic Fatty Liver Disease.
Aylin Tahmasebi et al. Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine 2023
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High prevalence of MUTYH associated polyposis among minority populations in Israel, due to rare founder pathogenic variants.
Gili Reznick Levi et al. Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver 2023
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Communicating PNPLA3 genetic risk status for NAFLD among Mexican-origin men.
Edgar A Villavicencio et al. Frontiers in public health 2023 101090101
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Original Article: prevalence and factors associated with liver fibrosis among first-degree relatives of Mexican Americans with hepatocellular carcinoma.
Sharpton Suzanne et al. Alimentary pharmacology & therapeutics 2023
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Two-dimensional Convolutional Neural Network Using Quantitative US for Noninvasive Assessment of Hepatic Steatosis in NAFLD.
Jeon Sun Kyung et al. Radiology 2023 221510
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Phenotypes of non-alcoholic fatty liver disease (NAFLD) and all-cause mortality: unsupervised machine learning analysis of NHANES III.
Carrillo-Larco Rodrigo M et al. BMJ open 2022 12(11) e067203
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Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics.
Robinson Jamie R et al. Obesity (Silver Spring, Md.) 2022
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Targeted Screening for Gaucher Disease in High Suspicion Patients and Clinical Profile of Screen Positives in a Large Pediatric Multispecialty Hospital.
Magar Suvarna et al. Cureus 2022 14(10) e29868
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Risk of advanced fibrosis in first-degree relatives of patients with nonalcoholic fatty liver disease.
Tamaki Nobuharu et al. The Journal of clinical investigation 2022 132(21)
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Evaluation of machine learning algorithms for predicting direct-acting antiviral treatment failure among patients with chronic hepatitis C infection.
Park Haesuk et al. Scientific reports 2022 12(1) 18094
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Genetic modifiers of penetrance to liver endpoints in HFE hemochromatosis: associations in a large community cohort.
Pilling Luke C et al. Hepatology (Baltimore, Md.) 2022
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Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.
Straw Isabel et al. BMJ health & care informatics 2022 29(1)
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Clinical Intervention to Reduce Dietary Sugar does not Impact Liver Fat in Latino Youth, Regardless of PNPLA3 Genotype: A Randomized Controlled Trial.
Schmidt Kelsey A et al. The Journal of nutrition 2022
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Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study.
Sarvestany Soren Sabet et al. The Lancet. Digital health 2022 4(3) e188-e199
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Predictive Modeling of Survival and Toxicity in Patients With Hepatocellular Carcinoma After Radiotherapy.
Chamseddine Ibrahim et al. JCO clinical cancer informatics 2022 6e2100169
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 25, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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