Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Sanja L. Antic"'
Autor:
Daniel J. Craig, Erin L. Crawford, Heidi Chen, Eric L. Grogan, Steven A. Deppen, Thomas Morrison, Sanja L. Antic, Pierre P. Massion, James C. Willey
Publikováno v:
BMC Cancer, Vol 23, Iss 1, Pp 1-10 (2023)
Abstract Background There is a need for biomarkers that improve accuracy compared with current demographic risk indices to detect individuals at the highest lung cancer risk. Improved risk determination will enable more effective lung cancer screenin
Externí odkaz:
https://doaj.org/article/132d8247a9a24f2c96428fa8c097bbfb
Autor:
Rafael Paez, Michael N. Kammer, Aneri Balar, Dhairya A. Lakhani, Michael Knight, Dianna Rowe, David Xiao, Brent E. Heideman, Sanja L. Antic, Heidi Chen, Sheau-Chiann Chen, Tobias Peikert, Kim L. Sandler, Bennett A. Landman, Stephen A. Deppen, Eric L. Grogan, Fabien Maldonado
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract A deep learning model (LCP CNN) for the stratification of indeterminate pulmonary nodules (IPNs) demonstrated better discrimination than commonly used clinical prediction models. However, the LCP CNN score is based on a single timepoint that
Externí odkaz:
https://doaj.org/article/7b78666c04264aa586a2c11b09157b75
Autor:
Kaiwen Xu, Mirza S. Khan, Thomas Z. Li, Riqiang Gao, Sanja L. Antic, Yuankai Huo, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman
Publikováno v:
Medical Imaging 2023: Image Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3b1bfefe7b5d15e2cce0dbd44f354328
https://doi.org/10.1117/12.2654018
https://doi.org/10.1117/12.2654018
Autor:
Erica C Nakajima, Michael P Frankland, Tucker F Johnson, Sanja L Antic, Heidi Chen, Sheau-Chiann Chen, Ronald A Karwoski, Ronald Walker, Bennett A Landman, Ryan D Clay, Brian J Bartholmai, Srinivasan Rajagopalan, Tobias Peikert, Pierre P Massion, Fabien Maldonado
Publikováno v:
PLoS ONE, Vol 13, Iss 6, p e0198118 (2018)
Lung adenocarcinoma (ADC), the most common lung cancer type, is recognized increasingly as a disease spectrum. To guide individualized patient care, a non-invasive means of distinguishing indolent from aggressive ADC subtypes is needed urgently. Comp
Externí odkaz:
https://doaj.org/article/526159792d044ac1a95ad2c359f6c425
Autor:
Kaiwen Xu, Thomas Li, Mirza S. Khan, Riqiang Gao, Sanja L. Antic, Yuankai Huo, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman
Publikováno v:
Medical Image Analysis. :102852
Field-of-view (FOV) tissue truncation beyond the lungs is common in routine lung screening computed tomography (CT). This poses limitations for opportunistic CT- based body composition (BC) assessment as key anatomical structures are missing. Traditi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8a877c4f33ef445678f6249e305e648e
https://doi.org/10.1016/j.media.2023.102852
https://doi.org/10.1016/j.media.2023.102852
Autor:
Riqiang Gao, Thomas Li, Yucheng Tang, Kaiwen Xu, Mirza Khan, Michael Kammer, Sanja L. Antic, Stephen Deppen, Yuankai Huo, Thomas A. Lasko, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman
Publikováno v:
Computers in biology and medicine. 150
Patients with indeterminate pulmonary nodules (IPN) with an intermediate to a high probability of lung cancer generally undergo invasive diagnostic procedures. Chest computed tomography image and clinical data have been in estimating the pretest prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3b4d5400387556a3643d205a9cbc42a
https://pubmed.ncbi.nlm.nih.gov/36198225
https://pubmed.ncbi.nlm.nih.gov/36198225
Autor:
Alexander M. Kaizer, Dhairya A. Lakhani, Amanda Kussrow, Ronald C. Walker, Heidi Chen, Sheau-Chiann Chen, Aneri B. Balar, Shayan Mahapatra, Stephen A. Deppen, Joseph Bauza, Melissa L. New, Sanja L. Antic, Bennett A. Landman, Fabien Maldonado, Yoganand Balagurunathan, Brenda Diergaarde, Michael N. Kammer, Matthew B. Schabath, Anna E. Barón, Erin A. Hirsch, Udaykamal Barad, Jun Qian, Pierre P. Massion, Robert J. Gillies, Matthew J. Rioth, Avrum Spira, David O. Wilson, Kim L. Sandler, William J. Feser, Eric L. Grogan, Darryl J. Bornhop, Jolene Strong, York E. Miller, Rebekah L. Webster, Dianna J. Rowe, Ehab Billatos, Thomas Atwater, Chirayu Shah, Sherif Helmey
Publikováno v:
American journal of respiratory and critical care medicine. 204(11)
Rationale- Patients with indeterminate pulmonary nodules (IPNs) at risk of cancer undergo high rates of invasive, costly, and morbid procedures. Objectives: To train and externally validate a risk ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ae0cd3fdc6efb7b21ef6172022e6a56
https://pubmed.ncbi.nlm.nih.gov/35373720
https://pubmed.ncbi.nlm.nih.gov/35373720
Autor:
khushbu H. Patel, Michael N. Kammer, Dianna J. Rowe, Brent E. Heideman, Sanja L. antic, Fabien Maldonado
Publikováno v:
Cancer Research. 82:1426-1426
Introduction: Building quantitative radiomic prediction models to improve the accuracy of non-invasive diagnosis of indeterminate pulmonary nodules (IPNs) is challenging, as these models are trained with a heterogeneous cancer population. The differe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebf79a5622564906f244df3c1243ea6d
https://doi.org/10.1158/1538-7445.am2022-1426
https://doi.org/10.1158/1538-7445.am2022-1426
Autor:
Riqiang, Gao, Yuankai, Huo, Shunxing, Bao, Yucheng, Tang, Sanja L, Antic, Emily S, Epstein, Aneri B, Balar, Steve, Deppen, Alexis B, Paulson, Kim L, Sandler, Pierre P, Massion, Bennett A, Landman
Publikováno v:
Mach Learn Med Imaging
The field of lung nodule detection and cancer prediction has been rapidly developing with the support of large public data archives. Previous studies have largely focused cross-sectional (single) CT data. Herein, we consider longitudinal data. The Lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::951491e006170e29934b3ebad3551a58
https://pubmed.ncbi.nlm.nih.gov/34040283
https://pubmed.ncbi.nlm.nih.gov/34040283
Autor:
Sanja L. Antic, Yuankai Huo, Yucheng Tang, Michael N. Kammer, Steve Deppen, Riqiang Gao, Bennett A. Landman, Kaiwen Xu, Kim L. Sandler, Pierre P. Massion
Publikováno v:
Proc SPIE Int Soc Opt Eng
Clinical data elements (CDEs) (e.g., age, smoking history), blood markers and chest computed tomography (CT) structural features have been regarded as effective means for assessing lung cancer risk. These independent variables can provide complementa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9903c1734fe7bb238c6e72980ad8b77d
http://arxiv.org/abs/2010.09524
http://arxiv.org/abs/2010.09524
