341 related articles for article (PubMed ID: 36523640)
1. Visual Transformers and Convolutional Neural Networks for Disease Classification on Radiographs: A Comparison of Performance, Sample Efficiency, and Hidden Stratification.
Murphy ZR; Venkatesh K; Sulam J; Yi PH
Radiol Artif Intell; 2022 Nov; 4(6):e220012. PubMed ID: 36523640
[TBL] [Abstract][Full Text] [Related]
2. Detecting Glaucoma from Fundus Photographs Using Deep Learning without Convolutions: Transformer for Improved Generalization.
Fan R; Alipour K; Bowd C; Christopher M; Brye N; Proudfoot JA; Goldbaum MH; Belghith A; Girkin CA; Fazio MA; Liebmann JM; Weinreb RN; Pazzani M; Kriegman D; Zangwill LM
Ophthalmol Sci; 2023 Mar; 3(1):100233. PubMed ID: 36545260
[TBL] [Abstract][Full Text] [Related]
3. Attention-based Saliency Maps Improve Interpretability of Pneumothorax Classification.
Wollek A; Graf R; Čečatka S; Fink N; Willem T; Sabel BO; Lasser T
Radiol Artif Intell; 2023 Mar; 5(2):e220187. PubMed ID: 37035429
[TBL] [Abstract][Full Text] [Related]
4. Development and Validation of a Convolutional Neural Network Model to Predict a Pathologic Fracture in the Proximal Femur Using Abdomen and Pelvis CT Images of Patients With Advanced Cancer.
Joo MW; Ko T; Kim MS; Lee YS; Shin SH; Chung YG; Lee HK
Clin Orthop Relat Res; 2023 Nov; 481(11):2247-2256. PubMed ID: 37615504
[TBL] [Abstract][Full Text] [Related]
5. Seeking an optimal approach for Computer-aided Diagnosis of Pulmonary Embolism.
Islam NU; Zhou Z; Gehlot S; Gotway MB; Liang J
Med Image Anal; 2024 Jan; 91():102988. PubMed ID: 37924750
[TBL] [Abstract][Full Text] [Related]
6. Rethinking Annotation Granularity for Overcoming Shortcuts in Deep Learning-based Radiograph Diagnosis: A Multicenter Study.
Luo L; Chen H; Xiao Y; Zhou Y; Wang X; Vardhanabhuti V; Wu M; Han C; Liu Z; Fang XHB; Tsougenis E; Lin H; Heng PA
Radiol Artif Intell; 2022 Sep; 4(5):e210299. PubMed ID: 36204545
[TBL] [Abstract][Full Text] [Related]
7. Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.
Hendrix N; Scholten E; Vernhout B; Bruijnen S; Maresch B; de Jong M; Diepstraten S; Bollen S; Schalekamp S; de Rooij M; Scholtens A; Hendrix W; Samson T; Sharon Ong LL; Postma E; van Ginneken B; Rutten M
Radiol Artif Intell; 2021 Jul; 3(4):e200260. PubMed ID: 34350413
[TBL] [Abstract][Full Text] [Related]
8. MuSiC-ViT: A multi-task Siamese convolutional vision transformer for differentiating change from no-change in follow-up chest radiographs.
Cho K; Kim J; Kim KD; Park S; Kim J; Yun J; Ahn Y; Oh SY; Lee SM; Seo JB; Kim N
Med Image Anal; 2023 Oct; 89():102894. PubMed ID: 37562256
[TBL] [Abstract][Full Text] [Related]
9. Application of deep learning-based computer-aided detection system: detecting pneumothorax on chest radiograph after biopsy.
Park S; Lee SM; Kim N; Choe J; Cho Y; Do KH; Seo JB
Eur Radiol; 2019 Oct; 29(10):5341-5348. PubMed ID: 30915557
[TBL] [Abstract][Full Text] [Related]
10. Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study.
Zech JR; Badgeley MA; Liu M; Costa AB; Titano JJ; Oermann EK
PLoS Med; 2018 Nov; 15(11):e1002683. PubMed ID: 30399157
[TBL] [Abstract][Full Text] [Related]
11. Convolutional Neural Networks (CNNs) for Pneumonia Classification on Pediatric Chest Radiographs.
Saboo YS; Kapse S; Prasanna P
Cureus; 2023 Aug; 15(8):e44130. PubMed ID: 37753018
[TBL] [Abstract][Full Text] [Related]
12. The Effect of Image Resolution on Deep Learning in Radiography.
Sabottke CF; Spieler BM
Radiol Artif Intell; 2020 Jan; 2(1):e190015. PubMed ID: 33937810
[TBL] [Abstract][Full Text] [Related]
13. Lightweight Visual Transformers Outperform Convolutional Neural Networks for Gram-Stained Image Classification: An Empirical Study.
Kim HE; Maros ME; Miethke T; Kittel M; Siegel F; Ganslandt T
Biomedicines; 2023 Apr; 11(5):. PubMed ID: 37239004
[TBL] [Abstract][Full Text] [Related]
14. Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.
Pan I; Agarwal S; Merck D
J Digit Imaging; 2019 Oct; 32(5):888-896. PubMed ID: 30838482
[TBL] [Abstract][Full Text] [Related]
15. Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning.
Kim YG; Lee SM; Lee KH; Jang R; Seo JB; Kim N
Eur Radiol; 2020 Sep; 30(9):4943-4951. PubMed ID: 32350657
[TBL] [Abstract][Full Text] [Related]
16. Development and Validation of Artificial Intelligence-based Method for Diagnosis of Mitral Regurgitation from Chest Radiographs.
Ueda D; Ehara S; Yamamoto A; Iwata S; Abo K; Walston SL; Matsumoto T; Shimazaki A; Yoshiyama M; Miki Y
Radiol Artif Intell; 2022 Mar; 4(2):e210221. PubMed ID: 35391769
[TBL] [Abstract][Full Text] [Related]
17. Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.
Sjoding MW; Taylor D; Motyka J; Lee E; Co I; Claar D; McSparron JI; Ansari S; Kerlin MP; Reilly JP; Shashaty MGS; Anderson BJ; Jones TK; Drebin HM; Ittner CAG; Meyer NJ; Iwashyna TJ; Ward KR; Gillies CE
Lancet Digit Health; 2021 Jun; 3(6):e340-e348. PubMed ID: 33893070
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.
Heo SJ; Kim Y; Yun S; Lim SS; Kim J; Nam CM; Park EC; Jung I; Yoon JH
Int J Environ Res Public Health; 2019 Jan; 16(2):. PubMed ID: 30654560
[TBL] [Abstract][Full Text] [Related]
19. Assessment of Critical Feeding Tube Malpositions on Radiographs Using Deep Learning.
Singh V; Danda V; Gorniak R; Flanders A; Lakhani P
J Digit Imaging; 2019 Aug; 32(4):651-655. PubMed ID: 31073816
[TBL] [Abstract][Full Text] [Related]
20. Training and Validating a Deep Convolutional Neural Network for Computer-Aided Detection and Classification of Abnormalities on Frontal Chest Radiographs.
Cicero M; Bilbily A; Colak E; Dowdell T; Gray B; Perampaladas K; Barfett J
Invest Radiol; 2017 May; 52(5):281-287. PubMed ID: 27922974
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
