Artificial intelligence-based diagnosis of upper gastrointestinal subepithelial lesions on endoscopic ultrasonography images
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Takamichi Kuwahara | K. Furukawa | M. Ishigami | M. Fujishiro | N. Kakushima | Masanao Nakamura | T. Yamamura | E. Ohno | H. Kawashima | Kenichi Matsui | T. Ishikawa | Tsunaki Sawada | Keiko Maeda | E. Ishikawa | Satoshi Furune | Y. Sasaki | Takahiro Nishikawa | T. Obayashi | Daisuke Sakai | Daijuro Hayashi | Hideko Yamamoto | Koji Yamada | Keiko Hirai | H. Asai | Takahiro Marukawa | Takuma Komiyama
[1] Quoc V. Le,et al. EfficientNetV2: Smaller Models and Faster Training , 2021, ICML.
[2] D. Kim,et al. Application of A Convolutional Neural Network in The Diagnosis of Gastric Mesenchymal Tumors on Endoscopic Ultrasonography Images , 2020, Journal of clinical medicine.
[3] M. Caricato,et al. What About Gastric Schwannoma? A Review Article , 2020, Journal of Gastrointestinal Cancer.
[4] K. Ando,et al. Efficacy of endoscopic ultrasound with artificial intelligence for the diagnosis of gastrointestinal stromal tumors , 2020, Journal of Gastroenterology.
[5] Linda S. Lee,et al. EUS-guided fine-needle biopsy versus fine-needle aspiration in the diagnosis of subepithelial lesions: a large multicenter study. , 2020, Gastrointestinal endoscopy.
[6] T. Chinen,et al. Superiority of mucosal incision-assisted biopsy over ultrasound-guided fine needle aspiration biopsy in diagnosing small gastric subepithelial lesions: a propensity score matching analysis , 2019, BMC gastroenterology.
[7] Taghi M. Khoshgoftaar,et al. A survey on Image Data Augmentation for Deep Learning , 2019, Journal of Big Data.
[8] Takamichi Kuwahara,et al. Usefulness of Deep Learning Analysis for the Diagnosis of Malignancy in Intraductal Papillary Mucinous Neoplasms of the Pancreas , 2019, Clinical and translational gastroenterology.
[9] Ukihide Tateishi,et al. Distinction between benign and malignant breast masses at breast ultrasound using deep learning method with convolutional neural network , 2019, Japanese Journal of Radiology.
[10] Robin L. Jones,et al. Gastrointestinal stromal tumours: ESMO-EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up. , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.
[11] R. Grützmann,et al. Gastrointestinal schwannomas: a rare but important differential diagnosis of mesenchymal tumors of gastrointestinal tract , 2018, BMC Surgery.
[12] T. Koga,et al. Current clinical management of gastrointestinal stromal tumor , 2018, World journal of gastroenterology.
[13] M. Fujishiro,et al. Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images , 2018, Gastric Cancer.
[14] E. Finkelstein,et al. Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes , 2017, JAMA.
[15] Nicolas Chapados,et al. Real-time differentiation of adenomatous and hyperplastic diminutive colorectal polyps during analysis of unaltered videos of standard colonoscopy using a deep learning model , 2017, Gut.
[16] Amy Wang,et al. The role of endoscopy in subepithelial lesions of the GI tract. , 2017, Gastrointestinal endoscopy.
[17] S. Kim,et al. Endoscopic ultrasound without tissue acquisition has poor accuracy for diagnosing gastric subepithelial tumors , 2016, Medicine.
[18] Seiichi Hirota,et al. The standard diagnosis, treatment, and follow-up of gastrointestinal stromal tumors based on guidelines , 2015, Gastric Cancer.
[19] Geoffrey E. Hinton,et al. Deep Learning , 2015, Nature.
[20] Eun Hye Kim,et al. Impact of Periodic Endoscopy on Incidentally Diagnosed Gastric Gastrointestinal Stromal Tumors: Findings in Surgically Resected and Confirmed Lesions , 2015, Annals of Surgical Oncology.
[21] T. Koga,et al. Clinical usefulness of endoscopic ultrasound-guided fine needle aspiration for gastric subepithelial lesions smaller than 2 cm. , 2014, Journal of gastrointestinal and liver diseases : JGLD.
[22] Aaron C. Courville,et al. Generative adversarial networks , 2014, Commun. ACM.
[23] L. Larocca,et al. Fine-needle tissue acquisition from subepithelial lesions using a forward-viewing linear echoendoscope , 2013, Endoscopy.
[24] Heikki Joensuu,et al. Gastrointestinal stromal tumour , 2013, The Lancet.
[25] R. Takayanagi,et al. Mucosal-incision assisted biopsy for suspected gastric gastrointestinal stromal tumors. , 2013, World journal of gastrointestinal endoscopy.
[26] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[27] L. Voltaggio,et al. Gastric schwannoma: a clinicopathologic study of 51 cases and critical review of the literature. , 2012, Human pathology.
[28] W. Brugge,et al. Accuracy of EUS in the evaluation of small gastric subepithelial lesions. , 2010, Gastrointestinal endoscopy.
[29] D. Park,et al. Is it possible to differentiate gastric GISTs from gastric leiomyomas by EUS? , 2009, World journal of gastroenterology.
[30] M. Kimmey,et al. A prospective study comparing endoscopy and EUS in the evaluation of GI subepithelial masses. , 2005, Gastrointestinal endoscopy.
[31] S. Hirota,et al. Biological and clinical review of stromal tumors in the gastrointestinal tract. , 2000, Histology and histopathology.
[32] J. Hedenbro,et al. Endoscopic diagnosis of submucosal gastric lesions , 1991, Surgical Endoscopy.
[33] M. Enjoji,et al. Benign schwannoma of the gastrointestinal tract: a clinicopathologic and immunohistochemical study. , 1988, Human pathology.
[34] M. Fujishiro,et al. Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks. , 2019, Gastrointestinal endoscopy.
[35] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[36] Dong-Hyun Lee,et al. Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks , 2013 .
[37] M. Catalano,et al. Interobserver agreement for EUS in the evaluation and diagnosis of submucosal masses. , 2001, Gastrointestinal endoscopy.