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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

340 related items for PubMed ID: 29095675

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  • 3. Skeletal development of the hand and wrist: digital bone age companion-a suitable alternative to the Greulich and Pyle atlas for bone age assessment?
    Bunch PM, Altes TA, McIlhenny J, Patrie J, Gaskin CM.
    Skeletal Radiol; 2017 Jun; 46(6):785-793. PubMed ID: 28343328
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  • 4. The RSNA Pediatric Bone Age Machine Learning Challenge.
    Halabi SS, Prevedello LM, Kalpathy-Cramer J, Mamonov AB, Bilbily A, Cicero M, Pan I, Pereira LA, Sousa RT, Abdala N, Kitamura FC, Thodberg HH, Chen L, Shih G, Andriole K, Kohli MD, Erickson BJ, Flanders AE.
    Radiology; 2019 Feb; 290(2):498-503. PubMed ID: 30480490
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  • 5. Deep learning-based automated bone age estimation for Saudi patients on hand radiograph images: a retrospective study.
    Hamd ZY, Alorainy AI, Alharbi MA, Hamdoun A, Alkhedeiri A, Alhegail S, Absar N, Khandaker MU, Osman AFI.
    BMC Med Imaging; 2024 Aug 01; 24(1):199. PubMed ID: 39090563
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  • 6. Pediatric skeletal age: determination with neural networks.
    Gross GW, Boone JM, Bishop DM.
    Radiology; 1995 Jun 01; 195(3):689-95. PubMed ID: 7753995
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  • 7. Forensic age estimation for pelvic X-ray images using deep learning.
    Li Y, Huang Z, Dong X, Liang W, Xue H, Zhang L, Zhang Y, Deng Z.
    Eur Radiol; 2019 May 01; 29(5):2322-2329. PubMed ID: 30402703
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  • 9. Bone age determination using only the index finger: a novel approach using a convolutional neural network compared with human radiologists.
    Reddy NE, Rayan JC, Annapragada AV, Mahmood NF, Scheslinger AE, Zhang W, Kan JH.
    Pediatr Radiol; 2020 Apr 01; 50(4):516-523. PubMed ID: 31863193
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  • 11. Computerized Bone Age Estimation Using Deep Learning Based Program: Evaluation of the Accuracy and Efficiency.
    Kim JR, Shim WH, Yoon HM, Hong SH, Lee JS, Cho YA, Kim S.
    AJR Am J Roentgenol; 2017 Dec 01; 209(6):1374-1380. PubMed ID: 28898126
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  • 12. Construction of artificial intelligence system of carpal bone age for Chinese children based on China-05 standard.
    Zhao X, Zhang M, Cheng M, Yue X, Li W, Li C.
    Med Phys; 2022 May 01; 49(5):3223-3232. PubMed ID: 35181886
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  • 13. Assessment of rapidly advancing bone age during puberty on elbow radiographs using a deep neural network model.
    Ahn KS, Bae B, Jang WY, Lee JH, Oh S, Kim BH, Lee SW, Jung HW, Lee JW, Sung J, Jung KH, Kang CH, Lee SH.
    Eur Radiol; 2021 Dec 01; 31(12):8947-8955. PubMed ID: 34115194
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  • 14. Automated semantic labeling of pediatric musculoskeletal radiographs using deep learning.
    Yi PH, Kim TK, Wei J, Shin J, Hui FK, Sair HI, Hager GD, Fritz J.
    Pediatr Radiol; 2019 Jul 01; 49(8):1066-1070. PubMed ID: 31041454
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  • 19. Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.
    Tajmir SH, Lee H, Shailam R, Gale HI, Nguyen JC, Westra SJ, Lim R, Yune S, Gee MS, Do S.
    Skeletal Radiol; 2019 Feb 01; 48(2):275-283. PubMed ID: 30069585
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  • 20. Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression.
    Van Steenkiste T, Ruyssinck J, Janssens O, Vandersmissen B, Vandecasteele F, Devolder P, Achten E, Van Hoecke S, Deschrijver D, Dhaene T.
    Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul 01; 2018():674-677. PubMed ID: 30440486
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