Thy-DAMP: deep artificial neural network model for prediction of thyroid cancer mortality

Mazzaferri EL (2007) Management of low-risk differentiated thyroid cancer. Endocr Pract 13(5):498–512

Article  PubMed  Google Scholar 

Morris LG, Myssiorek D (2010) Improved detection does not fully explain the rising incidence of well-differentiated thyroid cancer: a population-based analysis. Am J Surg 200(4):454–461

Article  PubMed  PubMed Central  Google Scholar 

Chen AY, Jemal A, Ward EM (2009) Increasing incidence of differentiated thyroid cancer in the United States, 1988–2005. Cancer: Interdisciplinary Int J Am Cancer Soc 115(16):3801–3807

Article  Google Scholar 

Tuttle RM (2008) Risk-adapted management of thyroid cancer. Endocr Pract 14(6):764–774

Article  PubMed  Google Scholar 

Ohle R, O’Reilly F, O’Brien KK, Fahey T, Dimitrov BD (2011) The Alvarado score for predicting acute appendicitis: a systematic review. BMC Med 9:1–13

Article  Google Scholar 

King MR (2023) The future of AI in medicine: a perspective from a Chatbot. Ann Biomed Eng 51(2):291–295

Article  PubMed  Google Scholar 

Samek W, Montavon G, Lapuschkin S, Anders CJ, Müller K-R (2021) Explaining deep neural networks and beyond: a review of methods and applications. Proc IEEE 109(3):247–278

Article  Google Scholar 

Thomas J, Haertling T (2020) AIBx, artificial intelligence model to risk stratify thyroid nodules. Thyroid 30(6):878–884

Article  PubMed  Google Scholar 

Bini F, Pica A, Azzimonti L, Giusti A, Ruinelli L, Marinozzi F et al (2021) Artificial intelligence in thyroid field—a comprehensive review. Cancers 13(19):4740

Article  PubMed  PubMed Central  Google Scholar 

Peng S, Liu Y, Lv W, Liu L, Zhou Q, Yang H et al (2021) Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study. Lancet Digit Health 3(4):e250–e9

Article  CAS  PubMed  Google Scholar 

Wildman-Tobriner B, Buda M, Hoang JK, Middleton WD, Thayer D, Short RG et al (2019) Using artificial intelligence to revise ACR TI-RADS risk stratification of thyroid nodules: diagnostic accuracy and utility. Radiology 292(1):112–119

Article  PubMed  Google Scholar 

Doll KM, Rademaker A, Sosa JA (2018) Practical guide to surgical data sets: surveillance, epidemiology, and end results (SEER) database. JAMA Surg 153(6):588–589

Article  PubMed  Google Scholar 

Ying X (2019) An overview of overfitting and its solutions. Journal of physics: Conference series: IOP Publishing; p. 022022

Borzooei S, Briganti G, Golparian M, Lechien JR, Tarokhian A (2024) Machine learning for risk stratification of thyroid cancer patients: a 15-year cohort study. Eur Arch Otorhinolaryngol 281(4):2095–2104

Article  PubMed  Google Scholar 

Seger C (2018) An investigation of categorical variable encoding techniques in machine learning: binary versus one-hot and feature hashing

Hossin M, Sulaiman MN (2015) A review on evaluation metrics for data classification evaluations. Int J data Min Knowl Manage Process 5(2):1

Article  Google Scholar 

Rufibach K (2010) Use of Brier score to assess binary predictions. J Clin Epidemiol 63(8):938–939

Article  PubMed  Google Scholar 

Hao J, Ho TK (2019) Machine learning made easy: a review of scikit-learn package in python programming language. J Educational Behav Stat 44(3):348–361

Article  Google Scholar 

Bisong E, Bisong E (2019) Matplotlib and seaborn. Building machine learning and deep learning models on google cloud platform: A comprehensive guide for beginners. :151 – 65

Ketkar N, Ketkar N (2017) Introduction to keras. Deep learning with python: a hands-on introduction. :97–111

Cortes C, Mohri M, Rostamizadeh A (2012) L2 regularization for learning kernels. arXiv Preprint arXiv :12052653

Xie X, Zhou P, Li H, Lin Z, Yan S, Adan (2022) Adaptive nesterov momentum algorithm for faster optimizing deep models. arXiv Preprint arXiv :220806677

Yeung M, Sala E, Schönlieb C-B, Rundo L (2022) Unified focal loss: generalising dice and cross entropy-based losses to handle class imbalanced medical image segmentation. Comput Med Imaging Graph 95:102026

Article  PubMed  PubMed Central  Google Scholar 

He H, Garcia EA (2009) Learning from imbalanced data. IEEE Trans Knowl Data Eng 21(9):1263–1284

Article  Google Scholar 

Pinsky MR, Bedoya A, Bihorac A, Celi L, Churpek M, Economou-Zavlanos NJ et al (2024) Use of artificial intelligence in critical care: opportunities and obstacles. Crit Care 28(1):113

Article  PubMed  PubMed Central  Google Scholar 

Lee D, Yoon SN (2021) Application of artificial intelligence-based technologies in the healthcare industry: opportunities and challenges. Int J Environ Res Public Health 18(1):271

Article  PubMed  PubMed Central  Google Scholar 

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