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For: Beek EJV, Mirsadraee S, Murchison JT. Lung cancer screening: Computed tomography or chest radiographs? World J Radiol 2015; 7(8): 189-193 [PMID: 26339461 DOI: 10.4329/wjr.v7.i8.189]
URL: https://www.wjgnet.com/1949-8470/full/v7/i8/189.htm
Number Citing Articles
1
Richard D. Pitcher. Radiology in Global Health2019; : 157 doi: 10.1007/978-3-319-98485-8_14
2
Sarfaraz Hussein, Kunlin Cao, Qi Song, Ulas Bagci. Information Processing in Medical ImagingLecture Notes in Computer Science 2017; 10265: 249 doi: 10.1007/978-3-319-59050-9_20
3
Francesca M Trovato, Daniela Catalano, Guglielmo M Trovato. Thoracic ultrasound: An adjunctive and valuable imaging tool in emergency, resource-limited settings and for a sustainable monitoring of patientsWorld Journal of Radiology 2016; 8(9): 775-784 doi: 10.4329/wjr.v8.i9.775
4
Deniz Nisham Anwer, Serkan Ozbay. Lung Cancer Classification and Detection Using Convolutional Neural NetworksProceedings of the 6th International Conference on Engineering & MIS 2020 2020; : 1 doi: 10.1145/3410352.3410822
5
Julio Mendoza, Helio Pedrini. Detection and classification of lung nodules in chest X‐ray images using deep convolutional neural networksComputational Intelligence 2020; 36(2): 370 doi: 10.1111/coin.12241
6
Chin Fung Kelvin Kan, Graham D. Unis, Luke Z. Li, Susan Gunn, Li Li, H. Peter Soyer, Mitchell S. Stark. Circulating Biomarkers for Early Stage Non-Small Cell Lung Carcinoma Detection: Supplementation to Low‐Dose Computed TomographyFrontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.555331
7
Yongzhong Ouyang, Junwen Liu, Baohua Nie, Naiping Dong, Xin Chen, Linfei Chen, YiPing Wei. Differential diagnosis of human lung tumors using surface desorption atmospheric pressure chemical ionization imaging mass spectrometryRSC Advances 2017; 7(88): 56044 doi: 10.1039/C7RA11839B
8
M. Haber, A. Drake, J. Nightingale. Is there an advantage to using computer aided detection for the early detection of pulmonary nodules within chest X-Ray imaging?Radiography 2020; 26(3): e170 doi: 10.1016/j.radi.2020.01.002
9
Luiz Carlos Corrêa da Silva, Alberto José de Araújo, Ângela Maria Dias de Queiroz, Maria da Penha Uchoa Sales, Maria Vera Cruz de Oliveira Castellano. Smoking control: challenges and achievementsJornal Brasileiro de Pneumologia 2016; 42(4): 290 doi: 10.1590/s1806-37562016000000145
10
Agne Krilaviciute, Hermann Brenner. Low positive predictive value of computed tomography screening for lung cancer irrespective of commonly employed definitions of target populationInternational Journal of Cancer 2021; 149(1): 58 doi: 10.1002/ijc.33522
11
Xuechen Li, Linlin Shen, Suhuai Luo. A Solitary Feature-Based Lung Nodule Detection Approach for Chest X-Ray RadiographsIEEE Journal of Biomedical and Health Informatics 2018; 22(2): 516 doi: 10.1109/JBHI.2017.2661805
12
Sean Carey, Sonja Kandel, Christin Farrell, John Kavanagh, TaeBong Chung, William Hamilton, Patrik Rogalla. Comparison of conventional chest x ray with a novel projection technique for ultra‐low dose CTMedical Physics 2021; 48(6): 2809 doi: 10.1002/mp.14142
13
Xuechen Li, Linlin Shen, Xinpeng Xie, Shiyun Huang, Zhien Xie, Xian Hong, Juan Yu. Multi-resolution convolutional networks for chest X-ray radiograph based lung nodule detectionArtificial Intelligence in Medicine 2020; 103: 101744 doi: 10.1016/j.artmed.2019.101744
14
H. De La Pena, A. Sharma, C. Glicksman, J. Joseph, M. Subesinghe, Z. Traill, C. Verrill, M. Sullivan, J. Redgwell, E. Bataillard, E. Pintus, N. Dallas, A. Gogbashian, M. Tuthill, A. Protheroe, M. Hall. No longer any role for routine follow-up chest x-rays in men with stage I germ cell cancerEuropean Journal of Cancer 2017; 84: 354 doi: 10.1016/j.ejca.2017.07.005
15
Imad Bou Akl, Nathalie K. Zgheib, Maroun Matar, Deborah Mukherji, Marco Bardus, Rihab Nasr. Primary care and pulmonary physicians’ knowledge and practice concerning screening for lung cancer in Lebanon, a middle‐income countryCancer Medicine 2021; 10(8): 2877 doi: 10.1002/cam4.3816
16
Yi Wang, Hao Zhang, Kum Ju Chae, Younhee Choi, Gong Yong Jin, Seok-Bum Ko. Novel convolutional neural network architecture for improved pulmonary nodule classification on computed tomographyMultidimensional Systems and Signal Processing 2020; 31(3): 1163 doi: 10.1007/s11045-020-00703-6