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Application of machine learning to ultrasound images to differentiate follicular neoplasms of the thyroid gland
Ilah Shin, Young Jae Kim, Kyunghwa Han, Eunjung Lee, Hye Jung Kim, Jung Hee Shin, Hee Jung Moon, Ji Hyun Youk, Kwang Gi Kim, Jin Young Kwak
Ultrasonography. 2020;39(3):257-265.   Published online 2020 February 29    DOI: https://doi.org/10.14366/usg.19069

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Application of machine learning to ultrasound images to differentiate follicular neoplasms of the thyroid gland
Ultrasonography. 2020;39(3):257-265   Crossref logo
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Abstract #853227: Application of Machine Learning Algorithms to Distinguish Follicular Adenoma from Follicular Thyroid Carcinoma by Medical Us Images
Endocrine Practice. 2020;26:310   Crossref logo
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The value of histomorphometric nuclear parameters in the diagnosis of well differentiated follicular carcinomas and follicular adenomas of the thyroid gland
Histopathology. 1999;34(5):453-461   Crossref logo
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Characteristics of thyroid follicular neoplasms
European Journal of Ultrasound. 1997;6:S6   Crossref logo
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Misclassification of cytologic diagnoses in patients with follicular lesions or follicular neoplasms of the thyroid gland
Cancer. 2003;99(5):318-319   Crossref logo
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Ultrasound characteristics of follicular and parafollicular thyroid neoplasms: diagnostic performance of artificial neural network
Thyroid Research. 2023;16(1):   Crossref logo
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Follicular Thyroid Carcinoma
Diagnostic Pathology: Pediatric Neoplasms. 2018;478-485   Crossref logo
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Misclassification of cytologic diagnoses in patients with follicular lesions or follicular neoplasms of the thyroid gland
Cancer. 2002;96(6):323-324   Crossref logo
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Stereology, flow cytometry, and immunohistochemistry of follicular neoplasms of the thyroid gland
Human Pathology. 1991;22(2):179-184   Crossref logo
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Follicular Thyroid Neoplasms
Atlas of Endocrine Pathology. 2014;55-62   Crossref logo
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