These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
154 related articles for article (PubMed ID: 38134726)
21. Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection. Jadhav A; Wong KCL; Wu JT; Moradi M; Syeda-Mahmood T AMIA Annu Symp Proc; 2020; 2020():593-601. PubMed ID: 33936433 [TBL] [Abstract][Full Text] [Related]
22. Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study. Seah JCY; Tang CHM; Buchlak QD; Holt XG; Wardman JB; Aimoldin A; Esmaili N; Ahmad H; Pham H; Lambert JF; Hachey B; Hogg SJF; Johnston BP; Bennett C; Oakden-Rayner L; Brotchie P; Jones CM Lancet Digit Health; 2021 Aug; 3(8):e496-e506. PubMed ID: 34219054 [TBL] [Abstract][Full Text] [Related]
23. Deep Learning-Based Computer-Aided Pneumothorax Detection Using Chest X-ray Images. Malhotra P; Gupta S; Koundal D; Zaguia A; Kaur M; Lee HN Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336449 [TBL] [Abstract][Full Text] [Related]
24. Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study. Taylor AG; Mielke C; Mongan J PLoS Med; 2018 Nov; 15(11):e1002697. PubMed ID: 30457991 [TBL] [Abstract][Full Text] [Related]
25. A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification. Al-Antari MA; Al-Masni MA; Choi MT; Han SM; Kim TS Int J Med Inform; 2018 Sep; 117():44-54. PubMed ID: 30032964 [TBL] [Abstract][Full Text] [Related]
26. Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization. Pasa F; Golkov V; Pfeiffer F; Cremers D; Pfeiffer D Sci Rep; 2019 Apr; 9(1):6268. PubMed ID: 31000728 [TBL] [Abstract][Full Text] [Related]
27. CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks. Wang H; Gu H; Qin P; Wang J PLoS One; 2020; 15(11):e0242013. PubMed ID: 33166371 [TBL] [Abstract][Full Text] [Related]
28. AI-driven deep convolutional neural networks for chest X-ray pathology identification. Albahli S; Ahmad Hassan Yar GN J Xray Sci Technol; 2022; 30(2):365-376. PubMed ID: 35068415 [TBL] [Abstract][Full Text] [Related]
29. Proposing a novel multi-instance learning model for tuberculosis recognition from chest X-ray images based on CNNs, complex networks and stacked ensemble. Khatibi T; Shahsavari A; Farahani A Phys Eng Sci Med; 2021 Mar; 44(1):291-311. PubMed ID: 33616887 [TBL] [Abstract][Full Text] [Related]
30. Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review. Santosh KC; Allu S; Rajaraman S; Antani S J Med Syst; 2022 Oct; 46(11):82. PubMed ID: 36241922 [TBL] [Abstract][Full Text] [Related]
31. Development of Debiasing Technique for Lung Nodule Chest X-ray Datasets to Generalize Deep Learning Models. Horry MJ; Chakraborty S; Pradhan B; Paul M; Zhu J; Loh HW; Barua PD; Acharya UR Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514877 [TBL] [Abstract][Full Text] [Related]
32. Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images. V J S; D JF Comput Math Methods Med; 2021; 2021():9269173. PubMed ID: 34795794 [TBL] [Abstract][Full Text] [Related]
33. Deep Learning for Diagnosis and Segmentation of Pneumothorax: The Results on the Kaggle Competition and Validation Against Radiologists. Tolkachev A; Sirazitdinov I; Kholiavchenko M; Mustafaev T; Ibragimov B IEEE J Biomed Health Inform; 2021 May; 25(5):1660-1672. PubMed ID: 32956067 [TBL] [Abstract][Full Text] [Related]
34. COV-MobNets: a mobile networks ensemble model for diagnosis of COVID-19 based on chest X-ray images. Eshraghi MA; Ayatollahi A; Shokouhi SB BMC Med Imaging; 2023 Jun; 23(1):83. PubMed ID: 37322450 [TBL] [Abstract][Full Text] [Related]
35. A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning. Khosravan N; Celik H; Turkbey B; Jones EC; Wood B; Bagci U Med Image Anal; 2019 Jan; 51():101-115. PubMed ID: 30399507 [TBL] [Abstract][Full Text] [Related]
36. [A survey on the application of convolutional neural networks in the diagnosis of occupational pneumoconiosis]. Wang Y; Wu J; Wu D Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2024 Apr; 41(2):413-420. PubMed ID: 38686425 [TBL] [Abstract][Full Text] [Related]
37. Deep Learning: An Update for Radiologists. Cheng PM; Montagnon E; Yamashita R; Pan I; Cadrin-Chênevert A; Perdigón Romero F; Chartrand G; Kadoury S; Tang A Radiographics; 2021; 41(5):1427-1445. PubMed ID: 34469211 [TBL] [Abstract][Full Text] [Related]
38. Medical Image Analysis using Convolutional Neural Networks: A Review. Anwar SM; Majid M; Qayyum A; Awais M; Alnowami M; Khan MK J Med Syst; 2018 Oct; 42(11):226. PubMed ID: 30298337 [TBL] [Abstract][Full Text] [Related]
39. 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]
40. An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach. Shah U; Abd-Alrazeq A; Alam T; Househ M; Shah Z Stud Health Technol Inform; 2020 Jun; 272():457-460. PubMed ID: 32604701 [TBL] [Abstract][Full Text] [Related] [Previous] [Next] [New Search]