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.
123 related articles for article (PubMed ID: 37842987)
41. Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging. Hsu ST; Su YJ; Hung CH; Chen MJ; Lu CH; Kuo CE BMC Med Inform Decis Mak; 2022 Nov; 22(1):298. PubMed ID: 36397100 [TBL] [Abstract][Full Text] [Related]
42. Deep learning-based classification of primary bone tumors on radiographs: A preliminary study. He Y; Pan I; Bao B; Halsey K; Chang M; Liu H; Peng S; Sebro RA; Guan J; Yi T; Delworth AT; Eweje F; States LJ; Zhang PJ; Zhang Z; Wu J; Peng X; Bai HX EBioMedicine; 2020 Dec; 62():103121. PubMed ID: 33232868 [TBL] [Abstract][Full Text] [Related]
43. Performance of novel deep learning network with the incorporation of the automatic segmentation network for diagnosis of breast cancer in automated breast ultrasound. Wang Q; Chen H; Luo G; Li B; Shang H; Shao H; Sun S; Wang Z; Wang K; Cheng W Eur Radiol; 2022 Oct; 32(10):7163-7172. PubMed ID: 35488916 [TBL] [Abstract][Full Text] [Related]
44. Using deep convolutional neural networks for multi-classification of thyroid tumor by histopathology: a large-scale pilot study. Wang Y; Guan Q; Lao I; Wang L; Wu Y; Li D; Ji Q; Wang Y; Zhu Y; Lu H; Xiang J Ann Transl Med; 2019 Sep; 7(18):468. PubMed ID: 31700904 [TBL] [Abstract][Full Text] [Related]
45. Using a Dual-Input Convolutional Neural Network for Automated Detection of Pediatric Supracondylar Fracture on Conventional Radiography. Choi JW; Cho YJ; Lee S; Lee J; Lee S; Choi YH; Cheon JE; Ha JY Invest Radiol; 2020 Feb; 55(2):101-110. PubMed ID: 31725064 [TBL] [Abstract][Full Text] [Related]
46. Comparison of radiologist versus natural language processing-based image annotations for deep learning system for tuberculosis screening on chest radiographs. Yi PH; Kim TK; Lin CT Clin Imaging; 2022 Jul; 87():34-37. PubMed ID: 35483162 [TBL] [Abstract][Full Text] [Related]
47. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs. Sim Y; Chung MJ; Kotter E; Yune S; Kim M; Do S; Han K; Kim H; Yang S; Lee DJ; Choi BW Radiology; 2020 Jan; 294(1):199-209. PubMed ID: 31714194 [TBL] [Abstract][Full Text] [Related]
48. Detection of Traumatic Pediatric Elbow Joint Effusion Using a Deep Convolutional Neural Network. England JR; Gross JS; White EA; Patel DB; England JT; Cheng PM AJR Am J Roentgenol; 2018 Dec; 211(6):1361-1368. PubMed ID: 30300006 [TBL] [Abstract][Full Text] [Related]
49. Deep learning driven diagnosis of malignant soft tissue tumors based on dual-modal ultrasound images and clinical indexes. Xie H; Zhang Y; Dong L; Lv H; Li X; Zhao C; Tian Y; Xie L; Wu W; Yang Q; Liu L; Sun D; Qiu L; Shen L; Zhang Y Front Oncol; 2024; 14():1361694. PubMed ID: 38846984 [TBL] [Abstract][Full Text] [Related]
50. An Intelligent Diagnostic Model for Melasma Based on Deep Learning and Multimode Image Input. Liu L; Liang C; Xue Y; Chen T; Chen Y; Lan Y; Wen J; Shao X; Chen J Dermatol Ther (Heidelb); 2023 Feb; 13(2):569-579. PubMed ID: 36577888 [TBL] [Abstract][Full Text] [Related]
51. Differentiating Benign from Malignant Renal Tumors Using T2- and Diffusion-Weighted Images: A Comparison of Deep Learning and Radiomics Models Versus Assessment from Radiologists. Xu Q; Zhu Q; Liu H; Chang L; Duan S; Dou W; Li S; Ye J J Magn Reson Imaging; 2022 Apr; 55(4):1251-1259. PubMed ID: 34462986 [TBL] [Abstract][Full Text] [Related]
52. Analyzing Lung Disease Using Highly Effective Deep Learning Techniques. Sriporn K; Tsai CF; Tsai CE; Wang P Healthcare (Basel); 2020 Apr; 8(2):. PubMed ID: 32340344 [TBL] [Abstract][Full Text] [Related]
53. Transfer Learning of the ResNet-18 and DenseNet-121 Model Used to Diagnose Intracranial Hemorrhage in CT Scanning. Zhou Q; Zhu W; Li F; Yuan M; Zheng L; Liu X Curr Pharm Des; 2022; 28(4):287-295. PubMed ID: 34961458 [TBL] [Abstract][Full Text] [Related]
54. Automatic classification of ultrasound breast lesions using a deep convolutional neural network mimicking human decision-making. Ciritsis A; Rossi C; Eberhard M; Marcon M; Becker AS; Boss A Eur Radiol; 2019 Oct; 29(10):5458-5468. PubMed ID: 30927100 [TBL] [Abstract][Full Text] [Related]
55. Ultrasound image-based deep learning to differentiate tubal-ovarian abscess from ovarian endometriosis cyst. Hu P; Gao Y; Zhang Y; Sun K Front Physiol; 2023; 14():1101810. PubMed ID: 36824470 [No Abstract] [Full Text] [Related]
56. Diagnosing Ovarian Cancer on MRI: A Preliminary Study Comparing Deep Learning and Radiologist Assessments. Saida T; Mori K; Hoshiai S; Sakai M; Urushibara A; Ishiguro T; Minami M; Satoh T; Nakajima T Cancers (Basel); 2022 Feb; 14(4):. PubMed ID: 35205735 [TBL] [Abstract][Full Text] [Related]
57. Thyroid ultrasound image classification using a convolutional neural network. Zhu YC; Jin PF; Bao J; Jiang Q; Wang X Ann Transl Med; 2021 Oct; 9(20):1526. PubMed ID: 34790732 [TBL] [Abstract][Full Text] [Related]
58. A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis. Kang D; Gweon HM; Eun NL; Youk JH; Kim JA; Son EJ Sci Rep; 2021 Dec; 11(1):23925. PubMed ID: 34907330 [TBL] [Abstract][Full Text] [Related]
59. Classification of fungal genera from microscopic images using artificial intelligence. Rahman MA; Clinch M; Reynolds J; Dangott B; Meza Villegas DM; Nassar A; Hata DJ; Akkus Z J Pathol Inform; 2023; 14():100314. PubMed ID: 37179570 [TBL] [Abstract][Full Text] [Related]
60. 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] [Previous] [Next] [New Search]