Search Results - "RASMUSSEN, Luke V"

Pragmatic reproducible research: improving the research process from raw data to results, bit by bit by Rasmussen, Luke V, Whitley, Eric W, Welty, Leah J

“…Reproducible research is the ability to recreate results given the same data, analytic code, and documentation. This definition of reproducibility has also…”
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PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability by Kirby, Jacqueline C, Speltz, Peter, Rasmussen, Luke V, Basford, Melissa, Gottesman, Omri, Peissig, Peggy L, Pacheco, Jennifer A, Tromp, Gerard, Pathak, Jyotishman, Carrell, David S, Ellis, Stephen B, Lingren, Todd, Thompson, Will K, Savova, Guergana, Haines, Jonathan, Roden, Dan M, Harris, Paul A, Denny, Joshua C

“…Objective Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine…”
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Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study by Adekkanattu, Prakash, Rasmussen, Luke V., Pacheco, Jennifer A., Kabariti, Joseph, Stone, Daniel J., Yu, Yue, Jiang, Guoqian, Luo, Yuan, Brandt, Pascal S., Xu, Zhenxing, Vekaria, Veer, Xu, Jie, Wang, Fei, Benda, Natalie C., Peng, Yifan, Goyal, Parag, Ahmad, Faraz S., Pathak, Jyotishman

“…Left ventricular ejection fraction (EF) is a key measure in the diagnosis and treatment of heart failure (HF) and many patients experience changes in EF…”
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Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records by Xu, Jie, Wang, Fei, Zang, Chengxi, Zhang, Hao, Niotis, Kellyann, Liberman, Ava L., Stonnington, Cynthia M., Ishii, Makoto, Adekkanattu, Prakash, Luo, Yuan, Mao, Chengsheng, Rasmussen, Luke V., Xu, Zhenxing, Brandt, Pascal, Pacheco, Jennifer A., Peng, Yifan, Jiang, Guoqian, Isaacson, Richard, Pathak, Jyotishman

“…The objective of this study was to investigate the potential association between the use of four frequently prescribed drug classes, namely antihypertensive…”
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Participant choices for return of genomic results in the eMERGE Network by Hoell, Christin, Wynn, Julia, Rasmussen, Luke V., Marsolo, Keith, Aufox, Sharon A., Chung, Wendy K., Connolly, John J., Freimuth, Robert R., Kochan, David, Hakonarson, Hakon, Harr, Margaret, Holm, Ingrid A., Kullo, Iftikhar J., Lammers, Philip E., Leppig, Kathleen A., Leslie, Nancy D., Myers, Melanie F., Sharp, Richard R., Smith, Maureen E., Prows, Cynthia A.

“…Purpose Secondary findings are typically offered in an all or none fashion when sequencing is used for clinical purposes. This study aims to describe the…”
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Provider perspectives on the integration of patient-reported outcomes in an electronic health record by Zhang, Renwen, Burgess, Eleanor R, Reddy, Madhu C, Rothrock, Nan E, Bhatt, Surabhi, Rasmussen, Luke V, Butt, Zeeshan, Starren, Justin B

“…Integrating patient-reported outcomes (PROs) into electronic health records (EHRs) can improve patient-provider communication and delivery of care. However,…”
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Addressing barriers in FAIR data practices for biomedical data by Hughes, Laura D., Tsueng, Ginger, DiGiovanna, Jack, Horvath, Thomas D., Rasmussen, Luke V., Savidge, Tor C., Stoeger, Thomas, Turkarslan, Serdar, Wu, Qinglong, Wu, Chunlei, Su, Andrew I., Pache, Lars

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Implementation of a culturally competent APOL1 genetic testing programme into living donor evaluation: A two-site, non-randomised, pre–post trial design by Smith, Justin D, Agrawal, Akansha, Wicklund, Catherine, Duquette, Debra, Friedewald, John, Rasmussen, Luke V, Gacki-Smith, Jessica, Tandon, S. Darius, Muhammad, Lutfiyya N, Yancy, Clyde W, Dong, Siyuan, Cooper, Matthew, Gilbert, Alexander, Shetty, Aneesha, Gordon, Elisa J

“…IntroductionWhile living donor (LD) kidney transplantation is the optimal treatment for patients with kidney failure, LDs assume a higher risk of future kidney…”
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Rapid identification of inflammatory arthritis and associated adverse events following immune checkpoint therapy: a machine learning approach by Tran, Steven D, Lin, Jean, Galvez, Carlos, Rasmussen, Luke V, Pacheco, Jennifer, Perottino, Giovanni M, Rahbari, Kian J, Miller, Charles D, John, Jordan D, Theros, Jonathan, Vogel, Kelly, Dinh, Patrick V, Malik, Sara, Ramzan, Umar, Tegtmeyer, Kyle, Mohindra, Nisha, Johnson, Jodi L, Luo, Yuan, Kho, Abel, Sosman, Jeffrey, Walunas, Theresa L

“…Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) poses a major clinical challenge to ICI therapy for cancer, with 13% of cases halting ICI…”
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Genomic Information for Clinicians in the Electronic Health Record: Lessons Learned From the Clinical Genome Resource Project and the Electronic Medical Records and Genomics Network by Williams, Marc S, Taylor, Casey Overby, Walton, Nephi A, Goehringer, Scott R, Aronson, Samuel, Freimuth, Robert R, Rasmussen, Luke V, Hall, Eric S, Prows, Cynthia A, Chung, Wendy K, Fedotov, Alexander, Nestor, Jordan, Weng, Chunhua, Rowley, Robb K, Wiesner, Georgia L, Jarvik, Gail P, Del Fiol, Guilherme

“…Genomic knowledge is being translated into clinical care. To fully realize the value, it is critical to place credible information in the hands of clinicians…”
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Review and evaluation of electronic health records-driven phenotype algorithm authoring tools for clinical and translational research by Xu, Jie, Rasmussen, Luke V, Shaw, Pamela L, Jiang, Guoqian, Kiefer, Richard C, Mo, Huan, Pacheco, Jennifer A, Speltz, Peter, Zhu, Qian, Denny, Joshua C, Pathak, Jyotishman, Thompson, William K, Montague, Enid

“…Objective To review and evaluate available software tools for electronic health record–driven phenotype authoring in order to identify gaps and needs for…”
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The epidemiology of errors in data capture, management, and analysis: A scoping review of retracted articles and retraction notices in clinical and translational research by Baldridge, Abigail S., Bellinger, Grace C., Fleming, Oriana M., Rasmussen, Luke V., Whitley, Eric W., Welty, Leah J.

“…Introduction:To better understand and prevent research errors, we conducted a first-of-its-kind scoping review of clinical and translational research articles…”
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Quality control procedures for genome-wide association studies by Turner, Stephen, Armstrong, Loren L, Bradford, Yuki, Carlson, Christopher S, Crawford, Dana C, Crenshaw, Andrew T, de Andrade, Mariza, Doheny, Kimberly F, Haines, Jonathan L, Hayes, Geoffrey, Jarvik, Gail, Jiang, Lan, Kullo, Iftikhar J, Li, Rongling, Ling, Hua, Manolio, Teri A, Matsumoto, Martha, McCarty, Catherine A, McDavid, Andrew N, Mirel, Daniel B, Paschall, Justin E, Pugh, Elizabeth W, Rasmussen, Luke V, Wilke, Russell A, Zuvich, Rebecca L, Ritchie, Marylyn D

“…Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the…”
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Using Machine Learning to Predict Antidepressant Treatment Outcome From Electronic Health Records by Xu, Zhenxing, Vekaria, Veer, Wang, Fei, Cukor, Judith, Su, Chang, Adekkanattu, Prakash, Brandt, Pascal, Jiang, Guoqian, Kiefer, Richard C., Luo, Yuan, Rasmussen, Luke V., Xu, Jie, Xiao, Yunyu, Alexopoulos, George, Pathak, Jyotishman

“…Highlights Longitudinal questionnaire data were used to measure antidepressant treatment outcome. Machine learning models were used to predict outcome from…”
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Developing a standardized but extendable framework to increase the findability of infectious disease datasets by Tsueng, Ginger, Cano, Marco A. Alvarado, Bento, José, Czech, Candice, Kang, Mengjia, Pache, Lars, Rasmussen, Luke V., Savidge, Tor C., Starren, Justin, Wu, Qinglong, Xin, Jiwen, Yeaman, Michael R., Zhou, Xinghua, Su, Andrew I., Wu, Chunlei, Brown, Liliana, Shabman, Reed S., Hughes, Laura D.

“…Biomedical datasets are increasing in size, stored in many repositories, and face challenges in FAIRness (findability, accessibility, interoperability,…”
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Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions by Yu, Jingzhi, Pacheco, Jennifer A, Ghosh, Anika S, Luo, Yuan, Weng, Chunhua, Shang, Ning, Benoit, Barbara, Carrell, David S, Carroll, Robert J, Dikilitas, Ozan, Freimuth, Robert R, Gainer, Vivian S, Hakonarson, Hakon, Hripcsak, George, Kullo, Iftikhar J, Mentch, Frank, Murphy, Shawn N, Peissig, Peggy L, Ramirez, Andrea H, Walton, Nephi, Wei, Wei-Qi, Rasmussen, Luke V

“…Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of…”
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331 Reusing EHR Phenotyping Algorithms in Practice: Developing the Colorado Diabetes EHR Research Repository (CODER) by Wilson, Melissa P., Mayer, David A., Rasmussen, Luke V., Khanal, Pramod, Nuriyeva, Maryam, McRae, Michael, Raghavan, Sridharan, Wiley, Laura K.

“…OBJECTIVES/GOALS: The rates of computational phenotyping algorithm reuse across health systems are low, leading to a proliferation of algorithms for the same…”
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Implementation of workflow engine technology to deliver basic clinical decision support functionality by Huser, Vojtech, Rasmussen, Luke V, Oberg, Ryan, Starren, Justin B

“…Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel…”
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Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data by Denny, Joshua C, Bastarache, Lisa, Ritchie, Marylyn D, Carroll, Robert J, Zink, Raquel, Mosley, Jonathan D, Field, Julie R, Pulley, Jill M, Ramirez, Andrea H, Bowton, Erica, Basford, Melissa A, Carrell, David S, Peissig, Peggy L, Kho, Abel N, Pacheco, Jennifer A, Rasmussen, Luke V, Crosslin, David R, Crane, Paul K, Pathak, Jyotishman, Bielinski, Suzette J, Pendergrass, Sarah A, Xu, Hua, Hindorff, Lucia A, Li, Rongling, Manolio, Teri A, Chute, Christopher G, Chisholm, Rex L, Larson, Eric B, Jarvik, Gail P, Brilliant, Murray H, McCarty, Catherine A, Kullo, Iftikhar J, Haines, Jonathan L, Crawford, Dana C, Masys, Daniel R, Roden, Dan M

“…When applied in large scale to electronic medical record data, the PheWAS approach replicates GWAS associations and reveals potentially new pleiotropic…”
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Cataract research using electronic health records by Waudby, Carol J, Berg, Richard L, Linneman, James G, Rasmussen, Luke V, Peissig, Peggy L, Chen, Lin, McCarty, Catherine A

“…The eMERGE (electronic MEdical Records and Genomics) network, funded by the National Human Genome Research Institute, is a national consortium formed to…”
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