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Carolyn Horst

Showing results (1-10 of 40) with videos related to

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Radiology|January 21, 2025
Building Rome: TNM Lung Cancer Staging and an Illustration of the Scientific MethodCarolyn Horst
Radiology|August 1, 2023
If Only We Had a Time Machine: Prior CT in Deep Learning for Lung Nodule PrognosticationCarolyn Horst, Mizuki Nishino
The British Journal of Radiology|September 20, 2022
Reporting and management of incidental lung findings on computed tomography: beyond lung nodulesCarolyn Horst, Shivani Patel, Arjun Nair
Thorax|March 8, 2019
Lessons on managing pulmonary nodules from NELSON: we have come a long wayCarolyn Horst, Arjun Nair, Sam M Janes
BJR Open|November 12, 2020
Differential diagnoses of fibrosing lung diseasesCarolyn Horst, Bahareh Gholipour, Arjun Nair, et al.
Chemosphere|December 6, 2012
Organic matter source discrimination by humic acid characterization: synchronous scan fluorescence spectroscopy and Ferrate(VI)Carolyn Horst, Virender K Sharma, J Clayton Baum, et al.
BJR Artificial Intelligence|May 1, 2026
The AI doctor will see you now: public perspectives on artificial intelligence in healthcareCarolyn Horst, Muhammad Aniq, Alice Taylor-Gee, et al.
Radiology. Artificial Intelligence|December 11, 2023
Patient Reidentification from Chest Radiographs: An Interpretable Deep Metric Learning Approach and Its ApplicationsMatthew S Macpherson, Charles E Hutchinson, Carolyn Horst, et al.
Thorax|August 15, 2020
Delivering low-dose CT screening for lung cancer: a pragmatic approachCarolyn Horst, Jennifer L Dickson, Sophie Tisi, et al.
Insights Into Imaging|November 19, 2023
Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT imagesRobert O'Shea, Thubeena Manickavasagar, Carolyn Horst, et al.
Pageof 4

Showing results (1-10 of 40) with videos related to

Sort By:
Pageof 4
Radiology|January 21, 2025
Building Rome: TNM Lung Cancer Staging and an Illustration of the Scientific MethodCarolyn Horst
Radiology|August 1, 2023
If Only We Had a Time Machine: Prior CT in Deep Learning for Lung Nodule PrognosticationCarolyn Horst, Mizuki Nishino
The British Journal of Radiology|September 20, 2022
Reporting and management of incidental lung findings on computed tomography: beyond lung nodulesCarolyn Horst, Shivani Patel, Arjun Nair
Thorax|March 8, 2019
Lessons on managing pulmonary nodules from NELSON: we have come a long wayCarolyn Horst, Arjun Nair, Sam M Janes
BJR Open|November 12, 2020
Differential diagnoses of fibrosing lung diseasesCarolyn Horst, Bahareh Gholipour, Arjun Nair, et al.
Chemosphere|December 6, 2012
Organic matter source discrimination by humic acid characterization: synchronous scan fluorescence spectroscopy and Ferrate(VI)Carolyn Horst, Virender K Sharma, J Clayton Baum, et al.
BJR Artificial Intelligence|May 1, 2026
The AI doctor will see you now: public perspectives on artificial intelligence in healthcareCarolyn Horst, Muhammad Aniq, Alice Taylor-Gee, et al.
Radiology. Artificial Intelligence|December 11, 2023
Patient Reidentification from Chest Radiographs: An Interpretable Deep Metric Learning Approach and Its ApplicationsMatthew S Macpherson, Charles E Hutchinson, Carolyn Horst, et al.
Thorax|August 15, 2020
Delivering low-dose CT screening for lung cancer: a pragmatic approachCarolyn Horst, Jennifer L Dickson, Sophie Tisi, et al.
Insights Into Imaging|November 19, 2023
Weakly supervised segmentation models as explainable radiological classifiers for lung tumour detection on CT imagesRobert O'Shea, Thubeena Manickavasagar, Carolyn Horst, et al.
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