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Nikos Sourlos

Showing results (1-10 of 7) with videos related to

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Seminars in Radiation Oncology|October 6, 2022
Standardization of Artificial Intelligence Development in RadiotherapyAlessia de Biase, Nikos Sourlos, Peter M A van Ooijen
Cancers|August 26, 2022
Possible Bias in Supervised Deep Learning Algorithms for CT Lung Nodule Detection and ClassificationNikos Sourlos, Jingxuan Wang, Yeshaswini Nagaraj, et al.
Computers in Biology and Medicine|December 28, 2023
Explainable machine learning model based on clinical factors for predicting the disappearance of indeterminate pulmonary nodulesJingxuan Wang, Nikos Sourlos, Marjolein Heuvelmans, et al.
Insights Into Imaging|October 14, 2024
Recommendations for the creation of benchmark datasets for reproducible artificial intelligence in radiologyNikos Sourlos, Rozemarijn Vliegenthart, Joao Santinha, et al.
Heliyon|July 24, 2023
Preparing CT imaging datasets for deep learning in lung nodule analysis: Insights from four well-known datasetsJingxuan Wang, Nikos Sourlos, Sunyi Zheng, et al.
European Journal of Radiology|October 1, 2025
Does BMI influence AI and human reader lung nodule detection in low-dose chest CT?Nikos Sourlos, Marcel van Tuinen, Grigory Sidorenkov, et al.
European Radiology Experimental|May 19, 2024
Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CTNikos Sourlos, GertJan Pelgrim, Hendrik Joost Wisselink, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Seminars in Radiation Oncology|October 6, 2022
Standardization of Artificial Intelligence Development in RadiotherapyAlessia de Biase, Nikos Sourlos, Peter M A van Ooijen
Cancers|August 26, 2022
Possible Bias in Supervised Deep Learning Algorithms for CT Lung Nodule Detection and ClassificationNikos Sourlos, Jingxuan Wang, Yeshaswini Nagaraj, et al.
Computers in Biology and Medicine|December 28, 2023
Explainable machine learning model based on clinical factors for predicting the disappearance of indeterminate pulmonary nodulesJingxuan Wang, Nikos Sourlos, Marjolein Heuvelmans, et al.
Insights Into Imaging|October 14, 2024
Recommendations for the creation of benchmark datasets for reproducible artificial intelligence in radiologyNikos Sourlos, Rozemarijn Vliegenthart, Joao Santinha, et al.
Heliyon|July 24, 2023
Preparing CT imaging datasets for deep learning in lung nodule analysis: Insights from four well-known datasetsJingxuan Wang, Nikos Sourlos, Sunyi Zheng, et al.
European Journal of Radiology|October 1, 2025
Does BMI influence AI and human reader lung nodule detection in low-dose chest CT?Nikos Sourlos, Marcel van Tuinen, Grigory Sidorenkov, et al.
European Radiology Experimental|May 19, 2024
Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CTNikos Sourlos, GertJan Pelgrim, Hendrik Joost Wisselink, et al.
Pageof 1