Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training

[1] Savadjiev P(2019)Demystification of AI-driven medical image interpretation: past, present and future Eur Radiol 29 1616-1624

[2] Chong J(2018)Deep learning in radiology Acad Radiol 25 1472-1480

[3] Dohan A(2019)Convolutional neural networks for radiologic images: a radiologist’s guide Radiology 290 590-606

[4] McBee MP(2018)Methodologic guide for evaluating clinical performance and effect of artificial intelligence technology for medical diagnosis and prediction Radiology 286 800-809

[5] Awan OA(2018)A computer-aided diagnosis system for thyroid nodules on ultrasonography: initial clinical experience Korean J Radiol 19 665-672

[6] Colucci AT(2018)Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators Eur Radiol 29 1978-1985

[7] Soffer S(2019)Real-world performance of computer-aided diagnosis system for thyroid nodules using ultrasonography Ultrasound Med Biol 45 2672-2678

[8] Ben-Cohen A(2019)Deep convolutional neural network models for the diagnosis of thyroid cancer The Lancet Oncology 20 e130-395

[9] Shimon O(2016)Ultrasonography diagnosis and imaging-based management of thyroid nodules: revised Korean Society of Thyroid Radiology Consensus Statement and Recommendations Korean J Radiol 17 370-381

[10] Amitai MM(2017)2015 American Thyroid Association Management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: what is new and what has changed? Cancer 123 372-161

[1] Savadjiev P(2019)Demystification of AI-driven medical image interpretation: past, present and future Eur Radiol 29 1616-1624

[2] Chong J(2018)Deep learning in radiology Acad Radiol 25 1472-1480

[3] Dohan A(2019)Convolutional neural networks for radiologic images: a radiologist’s guide Radiology 290 590-606

[4] McBee MP(2018)Methodologic guide for evaluating clinical performance and effect of artificial intelligence technology for medical diagnosis and prediction Radiology 286 800-809

[5] Awan OA(2018)A computer-aided diagnosis system for thyroid nodules on ultrasonography: initial clinical experience Korean J Radiol 19 665-672

[6] Colucci AT(2018)Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators Eur Radiol 29 1978-1985

[7] Soffer S(2019)Real-world performance of computer-aided diagnosis system for thyroid nodules using ultrasonography Ultrasound Med Biol 45 2672-2678

[8] Ben-Cohen A(2019)Deep convolutional neural network models for the diagnosis of thyroid cancer The Lancet Oncology 20 e130-395

[9] Shimon O(2016)Ultrasonography diagnosis and imaging-based management of thyroid nodules: revised Korean Society of Thyroid Radiology Consensus Statement and Recommendations Korean J Radiol 17 370-381

[10] Amitai MM(2017)2015 American Thyroid Association Management guidelines for adult patients with thyroid nodules and differentiated thyroid cancer: what is new and what has changed? Cancer 123 372-161