Euan A. Ashley
Stanford University
487 Papers
2.2K Citations
Euan A. Ashley is an academic researcher from Stanford University. The author has contributed to research in topics: Medicine & Hypertrophic cardiomyopathy. The author has an hindex of 75, co-authored 440 publications. Previous affiliations of Euan A. Ashley include VA Palo Alto Healthcare System & Veterans Health Administration.
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Papers
Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes
Rui Chen,George I. Mias,Jennifer Li-Pook-Than,Lihua Jiang,Hugo Y. K. Lam,Rong Chen,Elana Miriami,Konrad J. Karczewski,Manoj Hariharan,Frederick E. Dewey,Yong Cheng,Michael J. Clark,Hogune Im,Lukas Habegger,Suganthi Balasubramanian,Maeve O'Huallachain,Joel T. Dudley,Sara Hillenmeyer,Rajini R Haraksingh,Donald Sharon,Ghia Euskirchen,Phil Lacroute,Keith Bettinger,Alan P. Boyle,Maya Kasowski,Fabian Grubert,Scott Seki,Marco Garcia,Michelle Whirl-Carrillo,Mercedes Gallardo,Maria A. Blasco,Peter L. Greenberg,Phyllis Snyder,Teri E. Klein,Russ B. Altman,Atul J. Butte,Euan A. Ashley,Mark Gerstein,Kari C. Nadeau,Hua Tang,Michael Snyder +40 more
TL;DR: This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity and reveals extensive heteroallelic changes during healthy and disease states and an unexpected RNA editing mechanism.
1.3K
Guidelines for investigating causality of sequence variants in human disease
Daniel G. MacArthur,Teri A. Manolio,David Dimmock,Heidi L. Rehm,Jay Shendure,Gonçalo R. Abecasis,David R. Adams,Russ B. Altman,Stylianos E. Antonarakis,Euan A. Ashley,Jeffrey C. Barrett,Leslie G. Biesecker,Donald F. Conrad,Gregory M. Cooper,Nancy J. Cox,Mark J. Daly,Mark Gerstein,David Goldstein,Joel N. Hirschhorn,Suzanne M. Leal,Len A. Pennacchio,John A. Stamatoyannopoulos,Shamil R. Sunyaev,David Valle,Benjamin F. Voight,Wendy Winckler,Chris Gunter +26 more
TL;DR: The key challenges of assessing sequence variants in human disease are discussed, integrating both gene-level and variant-level support for causality and guidelines for summarizing confidence in variant pathogenicity are proposed.
Towards precision medicine
TL;DR: A deeper understanding of disease will be realized that will allow its targeting with much greater therapeutic precision, and global sharing of more accurate genotypic and phenotypic data will accelerate the determination of causality for novel genes or variants.
892
Artificial Intelligence in Cardiology
Kipp W. Johnson,Jessica Torres Soto,Benjamin S. Glicksberg,Khader Shameer,Riccardo Miotto,Mohsin Ali,Euan A. Ashley,Joel T. Dudley,Joel T. Dudley +8 more
TL;DR: This paper reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization, and describes the advent of deep learning and related methods collectively called unsupervised learning, which could be applied to enable precision cardiology and improve patient outcomes.
886
Video-based AI for beat-to-beat assessment of cardiac function.
David Ouyang,Bryan He,Amirata Ghorbani,Neal Yuan,Joseph E. Ebinger,Curtis P. Langlotz,Paul A. Heidenreich,Robert A. Harrington,David Liang,Euan A. Ashley,James Zou +10 more
TL;DR: A video-based deep learning algorithm that surpasses the performance of human experts in the critical tasks of segmenting the left ventricle, estimating ejection fraction and assessing cardiomyopathy is presented.