Full Text Journal Articles by
Author Jason H Moore

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Robust-ODAL: Learning from heterogeneous health systems without sharing patient-level data.

Jiayi Tong, Rui Duan, Ruowang Li, Martijn J Scheuemie, Jason H Moore, Yong Chen,

Electronic Health Records (EHR) contain extensive patient data on various health outcomes and risk predictors, providing an efficient and wide-reaching source for health research. Integrated EHR data can provide a larger sample size of the population to improve estimation and prediction accuracy. To overcome the obstacle of sharing patient-level data, ... Read more >>

Pac Symp Biocomput (Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing)
[2020, 25:695-706]

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Translational Bioinformatics: Biobanks in the Precision Medicine Era.

Marylyn D Ritchie, Jason H Moore, Ju Han Kim,

Translational bioinformatics (TBI) is focused on the integration of biomedical data science and informatics. This combination is extremely powerful for scientific discovery as well as translation into clinical practice. Several topics where TBI research is at the leading edge are 1) the use of large-scale biobanks linked to electronic health ... Read more >>

Pac Symp Biocomput (Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing)
[2020, 25:743-747]

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A maximum likelihood approach to electronic health record phenotyping using positive and unlabeled patients.

Lingjiao Zhang, Xiruo Ding, Yanyuan Ma, Naveen Muthu, Imran Ajmal, Jason H Moore, Daniel S Herman, Jinbo Chen,

OBJECTIVE:Phenotyping patients using electronic health record (EHR) data conventionally requires labeled cases and controls. Assigning labels requires manual medical chart review and therefore is labor intensive. For some phenotypes, identifying gold-standard controls is prohibitive. We developed an accurate EHR phenotyping approach that does not require labeled controls. MATERIALS AND METHODS:Our ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2019, :]

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Model selection for metabolomics: predicting diagnosis of coronary artery disease using automated machine learning (AutoML).

Alena Orlenko, Daniel Kofink, Leo-Pekka Lyytikäinen, Kjell Nikus, Pashupati Mishra, Pekka Kuukasjärvi, Pekka J Karhunen, Mika Kähönen, Jari O Laurikka, Terho Lehtimäki, Folkert W Asselberg, Jason H Moore,

MOTIVATION:Selecting the optimal machine learning (ML) model for a given dataset is often challenging. Automated ML (AutoML) has emerged as a powerful tool for enabling the automatic selection of ML methods and parameter settings for the prediction of biomedical endpoints. Here, we apply the tree-based pipeline optimization tool (TPOT) to ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2019, :]

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Prevalence and Characterization of Yoga Mentions in the Electronic Health Record.

Nadia M Penrod, Selah Lynch, Sunil Thomas, Nithya Seshadri, Jason H Moore,

BACKGROUND:There is a growing patient population using yoga as a therapeutic intervention, but little is known about how yoga interfaces with health care in clinical settings. PURPOSE:To characterize how yoga is documented at a large academic medical center and to systematically identify clinician-derived therapeutic use cases of yoga. METHODS:We designed ... Read more >>

J Am Board Fam Med (Journal of the American Board of Family Medicine : JABFM)
[2019, 32(6):790-800]

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An augmented estimation procedure for EHR-based association studies accounting for differential misclassification.

Jiayi Tong, Jing Huang, Jessica Chubak, Xuan Wang, Jason H Moore, Rebecca A Hubbard, Yong Chen,

OBJECTIVES:The ability to identify novel risk factors for health outcomes is a key strength of electronic health record (EHR)-based research. However, the validity of such studies is limited by error in EHR-derived phenotypes. The objective of this study was to develop a novel procedure for reducing bias in estimated associations ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2019, :]

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Embracing study heterogeneity for finding genetic interactions in large-scale research consortia.

Yulun Liu, Jing Huang, Ryan J Urbanowicz, Kun Chen, Elisabetta Manduchi, Casey S Greene, Jason H Moore, Paul Scheet, Yong Chen,

Genetic interactions have been recognized as a potentially important contributor to the heritability of complex diseases. Nevertheless, due to small effect sizes and stringent multiple-testing correction, identifying genetic interactions in complex diseases is particularly challenging. To address the above challenges, many genomic research initiatives collaborate to form large-scale consortia and ... Read more >>

Genet. Epidemiol. (Genetic epidemiology)
[2019, :]

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A regression framework to uncover pleiotropy in large-scale electronic health record data.

Ruowang Li, Rui Duan, Rachel L Kember, Daniel J Rader, Scott M Damrauer, Jason H Moore, Yong Chen,

OBJECTIVE:Pleiotropy, where 1 genetic locus affects multiple phenotypes, can offer significant insights in understanding the complex genotype-phenotype relationship. Although individual genotype-phenotype associations have been thoroughly explored, seemingly unrelated phenotypes can be connected genetically through common pleiotropic loci or genes. However, current analyses of pleiotropy have been challenged by both methodologic ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2019, 26(10):1083-1090]

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Integration of genetic and clinical information to improve imputation of data missing from electronic health records.

Ruowang Li, Yong Chen, Jason H Moore,

OBJECTIVE:Clinical data of patients' measurements and treatment history stored in electronic health record (EHR) systems are starting to be mined for better treatment options and disease associations. A primary challenge associated with utilizing EHR data is the considerable amount of missing data. Failure to address this issue can introduce significant ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2019, 26(10):1056-1063]

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EBIC: an open source software for high-dimensional and big data analyses.

Patryk Orzechowski, Jason H Moore,

MOTIVATION:In this paper, we present an open source package with the latest release of Evolutionary-based BIClustering (EBIC), a next-generation biclustering algorithm for mining genetic data. The major contribution of this paper is adding a full support for multiple graphics processing units (GPUs) support, which makes it possible to run efficiently ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2019, 35(17):3181-3183]

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Comparing drug safety of hepatitis C therapies using post-market data.

Jing Huang, Xinyuan Zhang, Jiayi Tong, Jingcheng Du, Rui Duan, Liu Yang, Jason H Moore, Cui Tao, Yong Chen,

BACKGROUND:Hepatitis C affects about 3 % of the world's population. In the United States, about 3.5 million have chronic hepatitis C, and it is the leading cause of liver cancer and the most common indication for liver transplantation. In the last decades, new advances in therapy have substantially increased the ... Read more >>

BMC Med Inform Decis Mak (BMC medical informatics and decision making)
[2019, 19(Suppl 4):147]

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Using Machine Learning on Home Health Care Assessments to Predict Fall Risk.

Yancy Lo, Selah F Lynch, Ryan J Urbanowicz, Randal S Olson, Ashley Z Ritter, Christina R Whitehouse, Melissa O'Connor, Susan K Keim, Margaret McDonald, Jason H Moore, Kathryn H Bowles,

Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardized fall risk assessments often require supplemental data collection and tend to have low specificity. We applied a random forest algorithm on readily available HHC data from the mandated ... Read more >>

Stud Health Technol Inform (Studies in health technology and informatics)
[2019, 264:684-688]

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Global identifiability of latent class models with applications to diagnostic test accuracy studies: A Gröbner basis approach.

Rui Duan, Ming Cao, Yang Ning, Mingfu Zhu, Bin Zhang, Aidan McDermott, Haitao Chu, Xiaohua Zhou, Jason H Moore, Joseph G Ibrahim, Daniel O Scharfstein, Yong Chen,

Identifiability of statistical models is a fundamental regularity condition that is required for valid statistical inference. Investigation of model identifiability is mathematically challenging for complex models such as latent class models. Jones et al. used Goodman's technique to investigate the identifiability of latent class models with applications to diagnostic tests ... Read more >>

Biometrics (Biometrics)
[2019, :]

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Exploration of a diversity of computational and statistical measures of association for genome-wide genetic studies.

Elisabetta Manduchi, Patryk R Orzechowski, Marylyn D Ritchie, Jason H Moore,

Background:The principal line of investigation in Genome Wide Association Studies (GWAS) is the identification of main effects, that is individual Single Nucleotide Polymorphisms (SNPs) which are associated with the trait of interest, independent of other factors. A variety of methods have been proposed to this end, mostly statistical in nature ... Read more >>

BioData Min (BioData mining)
[2019, 12:14]

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Scalable biclustering - the future of big data exploration?

Patryk Orzechowski, Krzysztof Boryczko, Jason H Moore,

Biclustering is a technique of discovering local similarities within data. For many years the complexity of the methods and parallelization issues limited its application to big data problems. With the development of novel scalable methods, biclustering has finally started to close this gap. In this paper we discuss the caveats ... Read more >>

Gigascience (GigaScience)
[2019, 8(7):]

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SNCA and mTOR Pathway Single Nucleotide Polymorphisms Interact to Modulate the Age at Onset of Parkinson's Disease.

Rubén Fernández-Santiago, Núria Martín-Flores, Francesca Antonelli, Catalina Cerquera, Verónica Moreno, Sara Bandres-Ciga, Elisabetta Manduchi, Eduard Tolosa, Andrew B Singleton, Jason H Moore, , María-Josep Martí, Mario Ezquerra, Cristina Malagelada,

BACKGROUND:Single nucleotide polymorphisms (SNPs) in the α-synuclein (SNCA) gene are associated with differential risk and age at onset (AAO) of both idiopathic and Leucine-rich repeat kinase 2 (LRRK2)-associated Parkinson's disease (PD). Yet potential combinatory or synergistic effects among several modulatory SNPs for PD risk or AAO remain largely underexplored. OBJECTIVES:The ... Read more >>

Mov. Disord. (Movement disorders : official journal of the Movement Disorder Society)
[2019, 34(9):1333-1344]

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Anticancer Therapy at the End of Life: Lessons From a Community Cancer Institute.

Shanthi Sivendran, Selah Lynch, Caitlyn McNaughton, Riley Wong, Sarah Svetec, Jason H Moore, Rachel Holliday, Randall A Oyer, Kristina Newport,

INTRODUCTION:Studies have shown aggressive cancer care at the end of life is associated with decreased quality of life, decreased median survival, and increased cost of care. This study describes the patients most likely to receive systemic anticancer therapy at the end of life in a community cancer institute. MATERIALS AND ... Read more >>

J Palliat Care (Journal of palliative care)
[2019, :825859719851484]

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Scaling tree-based automated machine learning to biomedical big data with a feature set selector.

Trang T Le, Weixuan Fu, Jason H Moore,

Automated machine learning (AutoML) systems are helpful data science assistants designed to scan data for novel features, select appropriate supervised learning models and optimize their parameters. For this purpose, Tree-based Pipeline Optimization Tool (TPOT) was developed using strongly typed genetic programming to recommend an optimized analysis pipeline for the data ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2019, :]

Cited: 1 time

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A comparison of two workflows for regulome and transcriptome-based prioritization of genetic variants associated with myocardial mass.

Elisabetta Manduchi, Daiane Hemerich, Jessica van Setten, Vinicius Tragante, Magdalena Harakalova, Jiayi Pei, Scott M Williams, Pim van der Harst, Folkert W Asselbergs, Jason H Moore,

A typical task arising from main effect analyses in a Genome Wide Association Study (GWAS) is to identify single nucleotide polymorphisms (SNPs), in linkage disequilibrium with the observed signals, that are likely causal variants and the affected genes. The affected genes may not be those closest to associating SNPs. Functional ... Read more >>

Genet. Epidemiol. (Genetic epidemiology)
[2019, 43(6):717-726]

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Mining Regional Imaging Genetic Associations via Voxel-wise Enrichment Analysis.

Xiaohui Yao, Shan Cong, Jingwen Yan, Shannon L Risacher, Andrew J Saykin, Jason H Moore, Li Shen,

Brain imaging genetics aims to reveal genetic effects on brain phenotypes, where most studies examine phenotypes defined on anatomical or functional regions of interest (ROIs) given their biologically meaningful annotation and modest dimensionality compared with voxel-wise approaches. Typical ROI-level measures used in these studies are summary statistics from voxel-wise measures ... Read more >>

IEEE EMBS Int Conf Biomed Health Inform (... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics)
[2019, 2019:]

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Why mind-body medicine is poised to set a new standard for clinical research.

Nadia M Penrod, Jason H Moore,

J Clin Epidemiol (Journal of clinical epidemiology)
[2019, 116:167-170]

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STatistical Inference Relief (STIR) feature selection.

Trang T Le, Ryan J Urbanowicz, Jason H Moore, Brett A McKinney,

MOTIVATION:Relief is a family of machine learning algorithms that uses nearest-neighbors to select features whose association with an outcome may be due to epistasis or statistical interactions with other features in high-dimensional data. Relief-based estimators are non-parametric in the statistical sense that they do not have a parameterized model with ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2019, 35(8):1358-1365]

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Testing the assumptions of parametric linear models: the need for biological data mining in disciplines such as human genetics.

Jason H Moore, Trudy F C Mackay, Scott M Williams,

BioData Min (BioData mining)
[2019, 12:6]

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Preparing next-generation scientists for biomedical big data: artificial intelligence approaches.

Jason H Moore, Mary Regina Boland, Pablo G Camara, Hannah Chervitz, Graciela Gonzalez, Blanca E Himes, Dokyoon Kim, Danielle L Mowery, Marylyn D Ritchie, Li Shen, Ryan J Urbanowicz, John H Holmes,

Personalized medicine is being realized by our ability to measure biological and environmental information about patients. Much of these data are being stored in electronic health records yielding big data that presents challenges for its management and analysis. Here, we review several areas of knowledge that are necessary for next-generation scientists ... Read more >>

Per Med (Personalized medicine)
[2019, 16(3):247-257]

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Integrative Functional Annotation of 52 Genetic Loci Influencing Myocardial Mass Identifies Candidate Regulatory Variants and Target Genes.

Daiane Hemerich, Jiayi Pei, Magdalena Harakalova, Jessica van Setten, Sander Boymans, Bas J Boukens, Igor R Efimov, Michelle Michels, Jolanda van der Velden, Aryan Vink, Caroline Cheng, Pim van der Harst, Jason H Moore, Michal Mokry, Vinicius Tragante, Folkert W Asselbergs,

BACKGROUND:Regulatory elements may be involved in the mechanisms by which 52 loci influence myocardial mass, reflected by abnormal amplitude and duration of the QRS complex on the ECG. Functional annotation thus far did not take into account how these elements are affected in disease context. METHODS:We generated maps of regulatory ... Read more >>

Circ Genom Precis Med (Circulation. Genomic and precision medicine)
[2019, 12(2):e002328]

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