A
Arturo Lopez Pineda
Researcher at Stanford University
Publications - 25
Citations - 235
Arturo Lopez Pineda is an academic researcher from Stanford University. The author has contributed to research in topics: Computer science & Breast cancer. The author has an hindex of 6, co-authored 21 publications receiving 96 citations. Previous affiliations of Arturo Lopez Pineda include University of Pittsburgh & Genentech.
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Journal ArticleDOI
Evaluating eligibility criteria of oncology trials using real-world data and AI
Ruishan Liu,Shemra Rizzo,Samuel Whipple,Navdeep Pal,Arturo Lopez Pineda,Michael Lu,Brandon Arnieri,Ying Lu,William B. Capra,Ryan Copping,James Zou +10 more
TL;DR: The authors' analyses reveal that many common criteria, including exclusions based on several laboratory values, had a minimal effect on the trial hazard ratios, and suggest that many patients who were not eligible under the original trial criteria could potentially benefit from the treatments.
Journal ArticleDOI
ClinGen Variant Curation Interface: a variant classification platform for the application of evidence criteria from ACMG/AMP guidelines
Christine G. Preston,Mathew W. Wright,Rao Madhavrao,Steven M. Harrison,Jennifer L. Goldstein,Xi Luo,Hannah Wand,Bryan Wulf,Gloria Cheung,Mark E. Mandell,Howard Tong,Shaung Cheng,Michael A. Iacocca,Arturo Lopez Pineda,Alice B. Popejoy,Karen P. Dalton,Jimmy Zhen,Selina Dwight,Lawrence J. Babb,Marina T. DiStefano,Julianne M. O’Daniel,Kristy Lee,Erin Rooney Riggs,Diane B. Zastrow,Jessica Mester,Deborah I. Ritter,Ronak Y. Patel,Sai Lakshmi Subramanian,Aleksander Milosavljevic,Jonathan S. Berg,Heidi L. Rehm,Sharon E. Plon,J. M. Cherry,Carlos Bustamante,Helio A. Costa +34 more
TL;DR: The ClinGen Variant Curation Interface (VCI) as mentioned in this paper is a global open-source variant classification platform for supporting the application of evidence criteria and classification of variants based on the ACMG/AMP variant classification guidelines.
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A study of the transferability of influenza case detection systems between two large healthcare systems.
Ye Ye,Michael M. Wagner,Gregory F. Cooper,Jeffrey P. Ferraro,Jeffrey P. Ferraro,Howard Su,Per H. Gesteland,Per H. Gesteland,Peter J. Haug,Peter J. Haug,Nicholas Millett,John M. Aronis,Andrew J. Nowalk,Victor M. Ruiz,Arturo Lopez Pineda,Lingyun Shi,Rudy Van Bree,Thomas Ginter,Fu-Chiang Tsui +18 more
TL;DR: High influenza case detection performance in two large healthcare systems in two geographically separated regions is demonstrated, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance.
Journal ArticleDOI
DeepTag: inferring diagnoses from veterinary clinical notes.
Allen Nie,Ashley M. Zehnder,Rodney L. Page,Yuhui Zhang,Arturo Lopez Pineda,Manuel A. Rivas,Carlos Bustamante,James Zou +7 more
TL;DR: A deep learning algorithm, DeepTag, which automatically infers diagnostic codes from veterinary free-text notes and enables automated disease annotation across a broad range of clinical diagnoses with minimal preprocessing.
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FasTag: Automatic text classification of unstructured medical narratives.
Guhan Venkataraman,Arturo Lopez Pineda,Oliver J. Bear Don't Walk,Ashley M. Zehnder,Sandeep Ayyar,Rodney L. Page,Carlos Bustamante,Manuel A. Rivas +7 more
TL;DR: This retrospective study aimed to automate the assignment of top-level International Classification of Diseases version 9 (ICD-9) codes to clinical records from human and veterinary data stores using minimal manual labor and feature curation.