Full Text Journal Articles by
Author Jason H Moore

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Learning from local to global: An efficient distributed algorithm for modeling time-to-event data.

Rui Duan, Chongliang Luo, Martijn J Schuemie, Jiayi Tong, C Jason Liang, Howard H Chang, Mary Regina Boland, Jiang Bian, Hua Xu, John H Holmes, Christopher B Forrest, Sally C Morton, Jesse A Berlin, Jason H Moore, Kevin B Mahoney, Yong Chen,

OBJECTIVE:We developed and evaluated a privacy-preserving One-shot Distributed Algorithm to fit a multicenter Cox proportional hazards model (ODAC) without sharing patient-level information across sites. MATERIALS AND METHODS:Using patient-level data from a single site combined with only aggregated information from other sites, we constructed a surrogate likelihood function, approximating the Cox ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2020, :]

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Recommendations to enhance rigor and reproducibility in biomedical research.

Jaqueline J Brito, Jun Li, Jason H Moore, Casey S Greene, Nicole A Nogoy, Lana X Garmire, Serghei Mangul,

Biomedical research depends increasingly on computational tools, but mechanisms ensuring open data, open software, and reproducibility are variably enforced by academic institutions, funders, and publishers. Publications may present software for which source code or documentation are or become unavailable; this compromises the role of peer review in evaluating technical strength ... Read more >>

Gigascience (GigaScience)
[2020, 9(6):]

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Ideas for how informaticians can get involved with COVID-19 research.

Jason H Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S Herman, Blanca E Himes, Rebecca A Hubbard, Dokyoon Kim, Jeffrey S Morris, Danielle L Mowery, Marylyn D Ritchie, Li Shen, Ryan Urbanowicz, John H Holmes,

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare for COVID-19 patients. Critical to this effort is the participation of informaticians who typically work on other basic science or ... Read more >>

BioData Min (BioData mining)
[2020, 13:3]

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Electronic health records and polygenic risk scores for predicting disease risk.

Ruowang Li, Yong Chen, Marylyn D Ritchie, Jason H Moore,

Accurate prediction of disease risk based on the genetic make-up of an individual is essential for effective prevention and personalized treatment. Nevertheless, to date, individual genetic variants from genome-wide association studies have achieved only moderate prediction of disease risk. The aggregation of genetic variants under a polygenic model shows promising ... Read more >>

Nat. Rev. Genet. (Nature reviews. Genetics)
[2020, :]

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Case contamination in electronic health records based case-control studies.

Lu Wang, Jill Schnall, Aeron Small, Rebecca A Hubbard, Jason H Moore, Scott M Damrauer, Jinbo Chen,

Clinically relevant information from electronic health records (EHRs) permits derivation of a rich collection of phenotypes. Unlike traditionally designed studies where scientific hypotheses are specified a priori before data collection, the true phenotype status of any given individual in EHR-based studies is not directly available. Structured and unstructured data elements ... Read more >>

Biometrics (Biometrics)
[2020, :]

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Multiple Plasma Biomarkers for Risk Stratification in Patients With Heart Failure and Preserved Ejection Fraction.

Julio A Chirinos, Alena Orlenko, Lei Zhao, Michael D Basso, Mary Ellen Cvijic, Zhuyin Li, Thomas E Spires, Melissa Yarde, Zhaoqing Wang, Dietmar A Seiffert, Stuart Prenner, Payman Zamani, Priyanka Bhattacharya, Anupam Kumar, Kenneth B Margulies, Bruce D Car, David A Gordon, Jason H Moore, Thomas P Cappola,

BACKGROUND:Better risk stratification strategies are needed to enhance clinical care and trial design in heart failure with preserved ejection fraction (HFpEF). OBJECTIVES:The purpose of this study was to assess the value of a targeted plasma multi-marker approach to enhance our phenotypic characterization and risk prediction in HFpEF. METHODS:In this study, ... Read more >>

J. Am. Coll. Cardiol. (Journal of the American College of Cardiology)
[2020, 75(11):1281-1295]

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Learning from electronic health records across multiple sites: A communication-efficient and privacy-preserving distributed algorithm.

Rui Duan, Mary Regina Boland, Zixuan Liu, Yue Liu, Howard H Chang, Hua Xu, Haitao Chu, Christopher H Schmid, Christopher B Forrest, John H Holmes, Martijn J Schuemie, Jesse A Berlin, Jason H Moore, Yong Chen,

OBJECTIVES:We propose a one-shot, privacy-preserving distributed algorithm to perform logistic regression (ODAL) across multiple clinical sites. MATERIALS AND METHODS:ODAL effectively utilizes the information from the local site (where the patient-level data are accessible) and incorporates the first-order (ODAL1) and second-order (ODAL2) gradients of the likelihood function from other sites to ... Read more >>

J Am Med Inform Assoc (Journal of the American Medical Informatics Association : JAMIA)
[2020, 27(3):376-385]

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

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 Asselbergs, 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))
[2020, 36(6):1772-1778]

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How Computational Experiments Can Improve Our Understanding of the Genetic Architecture of Common Human Diseases.

Jason H Moore, Randal S Olson, Peter Schmitt, Yong Chen, Elisabetta Manduchi,

Susceptibility to common human diseases such as cancer is influenced by many genetic and environmental factors that work together in a complex manner. The state of the art is to perform a genome-wide association study (GWAS) that measures millions of single-nucleotide polymorphisms (SNPs) throughout the genome followed by a one-SNP-at-a-time ... Read more >>

Artif. Life (Artificial life)
[2020, 26(1):23-37]

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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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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)
[2020, 27(2):244-253]

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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)
[2020, 27(1):119-126]

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

Trang T Le, Weixuan Fu, Jason H Moore,

MOTIVATION: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 programing (GP) to recommend an optimized analysis pipeline for the ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2020, 36(1):250-256]

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Regional imaging genetic enrichment analysis.

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

MOTIVATION: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 interpretation and modest dimensionality compared with voxelwise approaches. Typical ROI-level measures used in these studies are summary statistics from voxelwise measures ... Read more >>

Bioinformatics (Bioinformatics (Oxford, England))
[2020, 36(8):2554-2560]

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Correction to: Investigating the parameter space of evolutionary algorithms.

Moshe Sipper, Weixuan Fu, Karuna Ahuja, Jason H Moore,

[This corrects the article DOI: 10.1186/s13040-018-0164-x.]. ... Read more >>

BioData Min (BioData Mining)
[2019, 12:22]

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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)
[2020, 76(1):98-108]

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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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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)
[2020, 44(1):52-66]

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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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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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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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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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