Literature DB >> 29558310

Deep Learning Lends a Hand to Pediatric Radiology.

Ronald M Summers1.   

Abstract

Mesh：

Year:  2018        PMID： 29558310      PMCID： PMC5881636          DOI： 10.1148/radiol.2018172898

Source DB:  PubMed          Journal:  Radiology        ISSN： 0033-8419            Impact factor:   11.105


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  8 in total

Review 1.  Bone age assessment: automated techniques coming of age?

Authors:  R R van Rijn; H H Thodberg
Journal:  Acta Radiol       Date:  2013-11       Impact factor: 1.990

Review 2.  Progress in Fully Automated Abdominal CT Interpretation.

Authors:  Ronald M Summers
Journal:  AJR Am J Roentgenol       Date:  2016-04-21       Impact factor: 3.959

3.  Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Authors:  Paras Lakhani; Baskaran Sundaram
Journal:  Radiology       Date:  2017-04-24       Impact factor: 11.105

4.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

5.  Automated Critical Test Findings Identification and Online Notification System Using Artificial Intelligence in Imaging.

Authors:  Luciano M Prevedello; Barbaros S Erdal; John L Ryu; Kevin J Little; Mutlu Demirer; Songyue Qian; Richard D White
Journal:  Radiology       Date:  2017-07-03       Impact factor: 11.105

6.  Detection and diagnosis of colitis on computed tomography using deep convolutional neural networks.

Authors:  Jiamin Liu; David Wang; Le Lu; Zhuoshi Wei; Lauren Kim; Evrim B Turkbey; Berkman Sahiner; Nicholas A Petrick; Ronald M Summers
Journal:  Med Phys       Date:  2017-07-18       Impact factor: 4.071

7.  Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

Authors:  David B Larson; Matthew C Chen; Matthew P Lungren; Safwan S Halabi; Nicholas V Stence; Curtis P Langlotz
Journal:  Radiology       Date:  2017-11-02       Impact factor: 11.105

8.  Dermatologist-level classification of skin cancer with deep neural networks.

Authors:  Andre Esteva; Brett Kuprel; Roberto A Novoa; Justin Ko; Susan M Swetter; Helen M Blau; Sebastian Thrun
Journal:  Nature       Date:  2017-01-25       Impact factor: 49.962
  8 in total
  4 in total

Review 1.  Data harnessing to nurture the human mind for a tailored approach to the child.

Authors:  Saheli Chatterjee Misra; Kaushik Mukhopadhyay
Journal:  Pediatr Res       Date:  2022-09-30       Impact factor: 3.953

2.  Performance of deep learning-based algorithm for detection of ileocolic intussusception on abdominal radiographs of young children.

Authors:  Sungwon Kim; Haesung Yoon; Mi-Jung Lee; Myung-Joon Kim; Kyunghwa Han; Ja Kyung Yoon; Hyung Cheol Kim; Jaeseung Shin; Hyun Joo Shin
Journal:  Sci Rep       Date:  2019-12-19       Impact factor: 4.379

Review 3.  Artificial intelligence-aided decision support in paediatrics clinical diagnosis: development and future prospects.

Authors:  Yawen Li; Tiannan Zhang; Yushan Yang; Yuchen Gao
Journal:  J Int Med Res       Date:  2020-09       Impact factor: 1.671

Review 4.  [Artificial intelligence in image evaluation and diagnosis].

Authors:  Hans-Joachim Mentzel
Journal:  Monatsschr Kinderheilkd       Date:  2021-07-02       Impact factor: 0.323
  4 in total

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