Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Peggy Peissig"'
Autor:
Molly A Hall, John Wallace, Anastasia M Lucas, Yuki Bradford, Shefali S Verma, Bertram Müller-Myhsok, Kristin Passero, Jiayan Zhou, John McGuigan, Beibei Jiang, Sarah A Pendergrass, Yanfei Zhang, Peggy Peissig, Murray Brilliant, Patrick Sleiman, Hakon Hakonarson, John B Harley, Krzysztof Kiryluk, Kristel Van Steen, Jason H Moore, Marylyn D Ritchie
Publikováno v:
PLoS Genetics, Vol 17, Iss 6, p e1009534 (2021)
Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic
Externí odkaz:
https://doaj.org/article/b37fdfc15813491fa1c98bc3372f6d22
Publikováno v:
Data in Brief, Vol 17, Iss , Pp 71-75 (2018)
A fully-labeled image dataset provides a unique resource for reproducible research inquiries and data analyses in several computational fields, such as computer vision, machine learning and deep learning machine intelligence. With the present contrib
Externí odkaz:
https://doaj.org/article/b58013b14d774941ae4fb8590b8ee079
Autor:
Logan Dumitrescu, Marylyn D Ritchie, Joshua C Denny, Nihal M El Rouby, Caitrin W McDonough, Yuki Bradford, Andrea H Ramirez, Suzette J Bielinski, Melissa A Basford, High Seng Chai, Peggy Peissig, David Carrell, Jyotishman Pathak, Luke V Rasmussen, Xiaoming Wang, Jennifer A Pacheco, Abel N Kho, M Geoffrey Hayes, Martha Matsumoto, Maureen E Smith, Rongling Li, Rhonda M Cooper-DeHoff, Iftikhar J Kullo, Christopher G Chute, Rex L Chisholm, Gail P Jarvik, Eric B Larson, David Carey, Catherine A McCarty, Marc S Williams, Dan M Roden, Erwin Bottinger, Julie A Johnson, Mariza de Andrade, Dana C Crawford
Publikováno v:
PLoS ONE, Vol 12, Iss 2, p e0171745 (2017)
Resistant hypertension is defined as high blood pressure that remains above treatment goals in spite of the concurrent use of three antihypertensive agents from different classes. Despite the important health consequences of resistant hypertension, f
Externí odkaz:
https://doaj.org/article/b002153fafa945a8b48317afbc1af625
Publikováno v:
Algorithms, Vol 12, Iss 8, p 171 (2019)
With the rapid expansion of applied 3D computational vision, shape descriptors have become increasingly important for a wide variety of applications and objects from molecules to planets. Appropriate shape descriptors are critical for accurate (and e
Externí odkaz:
https://doaj.org/article/95d41369d4204eb9aeb8849b9ebf2474
Autor:
Andrew McDavid, Paul K Crane, Katherine M Newton, David R Crosslin, Wayne McCormick, Noah Weston, Kelly Ehrlich, Eugene Hart, Robert Harrison, Walter A Kukull, Carla Rottscheit, Peggy Peissig, Elisha Stefanski, Catherine A McCarty, Rebecca Lynn Zuvich, Marylyn D Ritchie, Jonathan L Haines, Joshua C Denny, Gerard D Schellenberg, Mariza de Andrade, Iftikhar Kullo, Rongling Li, Daniel Mirel, Andrew Crenshaw, James D Bowen, Ge Li, Debby Tsuang, Susan McCurry, Linda Teri, Eric B Larson, Gail P Jarvik, Chris S Carlson
Publikováno v:
PLoS ONE, Vol 8, Iss 6, p e63481 (2013)
The feasibility of using imperfectly phenotyped "silver standard" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped
Externí odkaz:
https://doaj.org/article/fa372963e31e49b88686fb2f6c50fec6
Autor:
Timothy M Herr, Suzette J Bielinski, Erwin Bottinger, Ariel Brautbar, Murray Brilliant, Christopher G Chute, Joshua Denny, Robert R Freimuth, Andrea Hartzler, Joseph Kannry, Isaac S Kohane, Iftikhar J Kullo, Simon Lin, Jyotishman Pathak, Peggy Peissig, Jill Pulley, James Ralston, Luke Rasmussen, Dan Roden, Gerard Tromp, Marc S Williams, Justin Starren
Publikováno v:
Journal of Pathology Informatics, Vol 6, Iss 1, Pp 46-46 (2015)
Genomic, proteomic, epigenomic, and other "omic" data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requi
Externí odkaz:
https://doaj.org/article/07a90dd6c8954dd4bc0c279e9835c694
Autor:
Timothy M Herr, Suzette J Bielinski, Erwin Bottinger, Ariel Brautbar, Murray Brilliant, Christopher G Chute, Beth L Cobb, Joshua C Denny, Hakon Hakonarson, Andrea L Hartzler, George Hripcsak, Joseph Kannry, Isaac S Kohane, Iftikhar J Kullo, Simon Lin, Shannon Manzi, Keith Marsolo, Casey Lynnette Overby, Jyotishman Pathak, Peggy Peissig, Jill Pulley, James Ralston, Luke Rasmussen, Dan M Roden, Gerard Tromp, Timothy Uphoff, Chunhua Weng, Wendy Wolf, Marc S Williams, Justin Starren
Publikováno v:
Journal of Pathology Informatics, Vol 6, Iss 1, Pp 50-50 (2015)
Background: Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presen
Externí odkaz:
https://doaj.org/article/b8b223e0710f4c67b15f41599205674d
We propose temporal Poisson square root graphical models (TPSQRs), a generalization of Poisson square root graphical models (PSQRs) specifically designed for modeling longitudinal event data. By estimating the temporal relationships for all possible
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cc799b2f0d4ed500165c2c2e785a7dd
http://arxiv.org/abs/2005.06462
http://arxiv.org/abs/2005.06462
Autor:
Shara I, Feld, Kaitlin M, Woo, Roxana, Alexandridis, Yirong, Wu, Jie, Liu, Peggy, Peissig, Adedayo A, Onitilo, Jennifer, Cox, C David, Page, Elizabeth S, Burnside
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2018
The predictive capability of combining demographic risk factors, germline genetic variants, and mammogram abnormality features for breast cancer risk prediction is poorly understood. We evaluated the predictive performance of combinations of demograp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::dd2412511ba30929696761be05873f76
https://pubmed.ncbi.nlm.nih.gov/30815167
https://pubmed.ncbi.nlm.nih.gov/30815167
Autor:
Yirong Wu, Ming Yuan, Jennifer Cox, Jie Yin, Peggy Peissig, David C. Page, Elizabeth S. Burnside, Ahmad P. Tafti, Jun Fan, Richard L. Berg
Publikováno v:
Medical Imaging: Image Perception, Observer Performance, and Technology Assessment
Improved prediction of the "most harmful" breast cancers that cause the most substantive morbidity and mortality would enable physicians to target more intense screening and preventive measures at those women who have the highest risk; however, such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a542c9c825d8c7320add98ca71e3d66
https://pubmed.ncbi.nlm.nih.gov/29706685
https://pubmed.ncbi.nlm.nih.gov/29706685