Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Sema Candemir"'
Publikováno v:
Tomography, Vol 8, Iss 4, Pp 1791-1803 (2022)
The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rapid data-driven approaches to facilitate clinical decision making. We examined a machine learning process to predict inpatient mortality among COVID-19
Externí odkaz:
https://doaj.org/article/d54f0abcfe574cf9855631af90a9a207
Autor:
Tao Peng, Thomas Canhao Xu, Yihuai Wang, Hailing Zhou, Sema Candemir, Wan Mimi Diyana Wan Zaki, Shanq-Jang Ruan, Jing Wang, Xinjian Chen
Publikováno v:
IEEE Access, Vol 8, Pp 73293-73306 (2020)
Accurate lung segmentation in chest Computed Tomography (CT) scans is a challenging problem because of variations in lung volume shape, susceptibility to partial volume effects that affect thin antero-posterior junction lines, and lack of contrast be
Externí odkaz:
https://doaj.org/article/1cba30e4c148499aadf7b755409096ee
Autor:
Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir, Daniel J. Boulter, Luciano M. Prevedello
Publikováno v:
Information, Vol 13, Iss 9, p 412 (2022)
Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurately distin
Externí odkaz:
https://doaj.org/article/0037e61eee1747138f878ed3cf39b76b
Publikováno v:
Applied Sciences, Vol 8, Iss 10, p 1715 (2018)
Pneumonia affects 7% of the global population, resulting in 2 million pediatric deaths every year. Chest X-ray (CXR) analysis is routinely performed to diagnose the disease. Computer-aided diagnostic (CADx) tools aim to supplement decision-making. Th
Externí odkaz:
https://doaj.org/article/5d4c102918364188a71984b75e44eca7
Publikováno v:
Alzheimer Disease & Associated Disorders. 35:1-7
In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whet
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1c6041bb41e344bc26fc21e08097dcd
https://doi.org/10.1097/wad.0000000000000406
https://doi.org/10.1097/wad.0000000000000406
Autor:
Thomas Canhao Xu, Tao Peng, Wan Mimi Diyana Wan Zaki, Yihuai Wang, Jing Wang, Xinjian Chen, Shanq-Jang Ruan, Hailing Zhou, Sema Candemir
Publikováno v:
IEEE Access, Vol 8, Pp 73293-73306 (2020)
Accurate lung segmentation in chest Computed Tomography (CT) scans is a challenging problem because of variations in lung volume shape, susceptibility to partial volume effects that affect thin antero-posterior junction lines, and lack of contrast be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a07a907d57d3743ff85326a7f11ebb1
https://ieeexplore.ieee.org/document/9066949/
https://ieeexplore.ieee.org/document/9066949/
Autor:
Thomas F. O'Donnell, Mutlu Demirer, Barbaros S. Erdal, Matthew T. Bigelow, Luciano M. Prevedello, Sema Candemir, Richard D. White, Engin Dikici, Jessica L. Carpenter, Abdul H. Halabi, Vikash Gupta, Mauricio S. Galizia
Publikováno v:
J Digit Imaging
Coronary computed tomography angiography (CCTA) evaluation of chest pain patients in an emergency department (ED) is considered appropriate. While a “negative” CCTA interpretation supports direct patient discharge from an ED, labor-intensive anal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be9776661bb6ee8cd2e1fbdaa7edc506
https://europepmc.org/articles/PMC8329136/
https://europepmc.org/articles/PMC8329136/
Publikováno v:
Radiol Artif Intell
Data-driven approaches have great potential to shape future practices in radiology. The most straightforward strategy to obtain clinically accurate models is to use large, well-curated and annotated datasets. However, patient privacy constraints, ted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15de4c17f2eb2d27d37f68d40a83760f
https://pubmed.ncbi.nlm.nih.gov/34870217
https://pubmed.ncbi.nlm.nih.gov/34870217
Predicting rate of cognitive decline at baseline using a deep neural network with multidata analysis
Autor:
Alzheimer’s Disease Neuroimaging Initiative, Xuan V. Nguyen, Matthew T. Bigelow, Barbaros S. Erdal, Sema Candemir, Richard D. White, Luciano M. Prevedello
Publikováno v:
J Med Imaging (Bellingham)
Purpose: Our study investigates whether a machine-learning-based system can predict the rate of cognitive decline in mildly cognitively impaired patients by processing only the clinical and imaging data collected at the initial visit. Approach: We bu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::447de9fbeeb515b4fe8fd654f2fd795c
https://pubmed.ncbi.nlm.nih.gov/32832577
https://pubmed.ncbi.nlm.nih.gov/32832577
Autor:
Feng Yang, Octavio Juarez-Espinosa, George R. Thoma, Sameer Antani, Meng Ding, Alex Rosenthal, Darrell E. Hurt, Sema Candemir, Stefan Jaeger, Les R. Folio, Lewis Kim, Mahdieh Poostchi, Andrei Gabrielian
Publikováno v:
International Journal of Computer Assisted Radiology and Surgery
Purpose Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decreasing over the last years, the rise of drug-resistant tuberculosis has reduced the chance of control
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f3782446431808c8f568c6efac1c773c
http://europepmc.org/articles/PMC6223762
http://europepmc.org/articles/PMC6223762