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    Academic Journal

    Source: Siberian journal of oncology; Том 23, № 5 (2024); 5-16 ; Сибирский онкологический журнал; Том 23, № 5 (2024); 5-16 ; 2312-3168 ; 1814-4861

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    Relation: https://www.siboncoj.ru/jour/article/view/3261/1265; Tran N.Q., Le B.H., Hoang C.K., Nguyen H.T., Thai T.T. Prevalence of thyroid nodules and associated clinical characteristics: fndings from a large sample of people undergoing health checkups at a university hospital in Vietnam. Risk Manag Healthc Policy. 2023; 16: 899–907. doi:10.2147/RMHP.S410964.; Bongiovanni M., Spitale A., Faquin W.C., Mazzucchelli L., Baloch Z.W. The Bethesda system for reporting thyroid cytopathology: a meta-analysis. Acta Cytol. 2012; 56(4): 333–39. doi:10.1159/000339959.; Kezlarian B., Lin O. Artifcial intelligence in thyroid fne needle aspiration biopsies. Acta Cytol. 2021; 65(4): 324–29. doi:10.1159/000512097.; Habchi Y., Himeur Y., Kheddar H., Boukabou A., Atalla S., Chouchane, A., Ouamane A., Mansoor W. AI in thyroid cancer diagnosis: techniques, trends, and future directions. Systems. 2023; 11(10): 519. doi:10.3390/systems11100519.; Litjens G., Kooi T., Bejnordi B.E., Setio A.A.A., Ciompi F., Ghafoorian M., van der Laak J.A.W.M., van Ginneken B., Sánchez C.I. A survey on deep learning in medical image analysis. Med Im- age Anal. 2017; 42: 60–88. doi:10.1016/J.MEDIA.2017.07.005.; Slabaugh G., Beltran L., Rizvi H., Deloukas P., Marouli E. Applications of machine and deep learning to thyroid cytology and histopathology: a review. Front Oncol. 2023; 13. doi:10.3389/FONC.2023.958310.; Wong C.M., Kezlarian B.E., Lin O. Current status of machine learning in thyroid cytopathology. J Pathol Inform. 2023; 14. doi:10.1016/J.JPI.2023.100309.; Sanyal P., Mukherjee T., Barui S., Das A., Gangopadhyay P. Artifcial intelligence in cytopathology: a neural network to iden tify papillary carcinoma on thyroid fne-needle aspiration cytology smears. J Pathol Inform. 2018; 9. doi:10.4103/JPI.JPI_43_18.; Guan Q., Wang Y., Ping B., Li D., Du J., Qin Y., Lu H., Wan X., Xiang J. Deep convolutional neural network VGG-16 model for diferential diagnosing of papillary thyroid carcinomas in cytological images: a pilot study. J Cancer. 2019; 10(20): 4876–82. doi:10.7150/JCA.28769.; Dov D., Kovalsky S.Z., Assaad S., Cohen J., Range D.E., Pendse A.A., Henao R., Carin L. Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Med Image Anal. 2021; 67. doi:10.1016/J.MEDIA.2020.101814.; Dov D., Elliott Range D., Cohen J., Bell J., Rocke D.J., Kahmke R.R., Weiss-Meilik A., Lee W.T., Henao R., Carin L., Kovalsky S.Z. Deep-learning-based screening and ancillary testing for thyroid cytopathology. Am J Pathol. 2023; 193(9): 1185–94. doi:10.1016/J.AJPATH.2023.05.011.; Dov D., Kovalsky S.Z., Cohen J., Range D.E., Henao R., Carin L. Thyroid cancer malignancy prediction from whole slide cytopathology images. Proc Mach Learn Res. 2019; 106: 553–70.; Elliott Range D.D., Dov D., Kovalsky S.Z., Henao R., Carin L., Cohen J. Application of a machine learning algorithm to predict malignancy in thyroid cytopathology. Cancer Cytopathol. 2020; 128(4): 287–95. doi:10.1002/CNCY.22238.; Duan W., Gao L., Liu J., Li C., Jiang P., Wang L., Chen H., Sun X., Cao D., Pang B., Li R., Liu S. Computer-assisted fneneedle aspiration cytology of thyroid using two-stage refned convolutional neural network. Electronics. 2022; 11(24). doi:10.3390/ELECTRONICS11244089.; Alabrak M.M.A., Megahed M., Alkhouly A.A., Mohammed A., Elfandy H., Tahoun N., Ismail H.A.R. Artificial intelligence role in subclassifying cytology of thyroid follicular neoplasm. Asian Pac J Cancer Prev. 2023; 24(4): 1379–87. doi:10.31557/APJCP.2023.24.4.1379.; Hirokawa M., Niioka H., Suzuki A., Abe M., Arai Y., Nagahara H., Miyauchi A., Akamizu T. Application of deep learning as an ancillary diagnostic tool for thyroid FNA cytology. Cancer Cytopathol. 2023; 131(4): 217–25. doi:10.1002/CNCY.22669.; Duc N.T., Lee Y.M., Park J.H., Lee B. An ensemble deep learning for automatic prediction of papillary thyroid carcinoma using fne needle aspiration cytology. Expert Syst Appl. 2022; 188(4). doi:10.1016/j.eswa.2021.115927.; Ali S.Z., Baloch Z.W., Cochand-Priollet B., Schmitt F.C., Vielh P., Vanderlaan P.A. The 2023 Bethesda system for reporting thyroid cytopathology. Thyroid. 2023; 33(9): 1039–44. doi:10.1089/THY.2023.0141.; https://www.siboncoj.ru/jour/article/view/3261

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    Academic Journal

    Source: Mìžnarodnij Endokrinologìčnij Žurnal, Vol 14, Iss 5, Pp 528-538 (2018)
    INTERNATIONAL JOURNAL OF ENDOCRINOLOGY; Том 14, № 5 (2018); 528-538
    Международный эндокринологический журнал-Mìžnarodnij endokrinologìčnij žurnal; Том 14, № 5 (2018); 528-538
    Міжнародний ендокринологічний журнал-Mìžnarodnij endokrinologìčnij žurnal; Том 14, № 5 (2018); 528-538

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    Academic Journal

    Contributors: The study was conducted with financial support for basic scientific research under the projects 0310-2014-0002, 0310-2015-0003, 0310-2015-0007, Фундаментальные научные исследования по темам 0310-2014-0002

    Source: Advances in Molecular Oncology; Vol 4, No 4 (2017); 24-31 ; Успехи молекулярной онкологии; Vol 4, No 4 (2017); 24-31 ; 2413-3787 ; 2313-805X

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  7. 7
    Academic Journal

    Source: Pathologia; Vol. 14 No. 1 (2017): Pathologia ; Патология; Том 14 № 1 (2017): Патологія ; Патологія; Том 14 № 1 (2017): Патологія ; 2310-1237 ; 2306-8027

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