D
David Qing
Researcher at University of California, Los Angeles
Publications - 8
Citations - 2548
David Qing is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Messenger RNA & Renal function. The author has an hindex of 8, co-authored 8 publications receiving 1900 citations. Previous affiliations of David Qing include UCLA Medical Center & Los Angeles Biomedical Research Institute.
Papers
More filters
Journal ArticleDOI
The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.
Samuel G. Armato,Geoffrey McLennan,Luc Bidaut,Michael F. McNitt-Gray,Charles R. Meyer,Anthony P. Reeves,Binsheng Zhao,Denise R. Aberle,Claudia I. Henschke,Eric A. Hoffman,Ella A. Kazerooni,Heber MacMahon,Edwin J. R. van Beek,David F. Yankelevitz,Alberto Biancardi,Peyton H. Bland,Matthew S. Brown,Roger Engelmann,Gary E. Laderach,Daniel Max,Richard C. Pais,David Qing,Rachael Y. Roberts,Amanda R. Smith,Adam Starkey,Poonam Batra,Philip Caligiuri,Ali Farooqi,Gregory W. Gladish,C. Matilda Jude,Reginald F. Munden,Iva Petkovska,Leslie E. Quint,Lawrence H. Schwartz,Baskaran Sundaram,Lori E. Dodd,Charles Fenimore,David Gur,Nicholas Petrick,John Freymann,Justin Kirby,Brian Hughes,Alessi Vande Casteele,Sangeeta Gupte,Maha Sallam,Michael D. Heath,Michael Kuhn,Ekta Dharaiya,Richard Burns,David Fryd,Marcos Salganicoff,Vikram Anand,Uri Shreter,Stephen Vastagh,Barbara Y. Croft,Laurence P. Clarke +55 more
TL;DR: The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus and is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.
Journal ArticleDOI
The Lung Image Database Consortium (LIDC) Data Collection Process for Nodule Detection and Annotation
Michael F. McNitt-Gray,Samuel G. Armato,Charles R. Meyer,Anthony P. Reeves,Geoffrey McLennan,Richie C. Pais,John Freymann,John Freymann,Matthew S. Brown,Roger Engelmann,Peyton H. Bland,Gary E. Laderach,Chris Piker,Junfeng Guo,Zaid J. Towfic,David Qing,David F. Yankelevitz,Denise R. Aberle,Edwin J. R. van Beek,Heber MacMahon,Ella A. Kazerooni,Barbara Y. Croft,Laurence P. Clarke +22 more
TL;DR: A unique data collection process was developed, tested, and implemented that allowed multiple readers at distributed sites to asynchronously review CT scans multiple times and captured the opinions of each reader regarding the location and spatial extent of lung nodules.
Journal ArticleDOI
The Lung Image Database Consortium (LIDC): An Evaluation of Radiologist Variability in the Identification of Lung Nodules on CT Scans
Samuel G. Armato,Michael F. McNitt-Gray,Anthony P. Reeves,Charles R. Meyer,Geoffrey McLennan,Denise R. Aberle,Ella A. Kazerooni,Heber MacMahon,Edwin J. R. van Beek,David F. Yankelevitz,Eric A. Hoffman,Claudia I. Henschke,Rachael Y. Roberts,Matthew S. Brown,Roger Engelmann,Richard C. Pais,Christopher W. Piker,David Qing,Masha Kocherginsky,Barbara Y. Croft,Laurence P. Clarke +20 more
TL;DR: The two-phase image annotation process yields improved agreement among radiologists in the interpretation of nodules >or=3 mm, Nevertheless, substantial variability remains across radiologist in the task of lung nodule identification.
Journal ArticleDOI
Evaluation of Lung MDCT Nodule Annotation Across Radiologists and Methods
Charles R. Meyer,Timothy D. Johnson,Geoffrey McLennan,Denise R. Aberle,Ella A. Kazerooni,Heber MacMahon,Brian F. Mullan,David F. Yankelevitz,Edwin J. R. van Beek,Samuel G. Armato,Michael F. McNitt-Gray,Anthony P. Reeves,David Gur,Claudia I. Henschke,Eric A. Hoffman,Peyton H. Bland,Gary E. Laderach,Richie C. Pais,David Qing,Chris Piker,Junfeng Guo,Adam Starkey,Daniel Max,Barbara Y. Croft,Laurence P. Clarke +24 more
TL;DR: Radiologists represent the major source of variance as compared with drawing tools independent of drawing metric used, and the random noise component is larger for the p-map analysis than for volume estimation, which appears to have more power to detect differences in radiologist-method combinations.
Journal ArticleDOI
L-carnitine ameliorates gentamicin-induced renal injury in rats
Joel D. Kopple,Hu Ding,Annamária Letoha,Béla Iványi,David Qing,Lázló Dux,Huiyuan Wang,Sandor Sonkodi +7 more
TL;DR: In rats receiving gentamicin, daily L-carnitine injections, particularly at 200 mg/kg/day, ameliorate the severity of renal cortical proximal tubular necrosis and maintain greater renal function.