Digital medicine has the capacity to affect all aspects of medicine, including disease prediction, prevention, diagnosis, treatment, and post-treatment management. In the field of thyroidology, researchers are also investigating potential applications of digital technology for the thyroid disease. Recent studies using artificial intelligence (AI)/machine learning (ML) have reported reasonable performance for the classification of thyroid nodules based on ultrasonographic (US) images. AI/ML-based methods have also shown good diagnostic accuracy for distinguishing between benign and malignant thyroid lesions based on cytopathologic findings. Assistance from AI/ML methods could overcome the limitations of conventional thyroid US and fine-needle aspiration cytology. A web-based database has been developed for thyroid cancer care. In addition to its role as a nationwide registry of thyroid cancer, it is expected to serve as a clinical platform to facilitate better thyroid cancer care and as a research platform providing comprehensive disease-specific big data. Evidence has been found that biosignal monitoring with wearable devices may predict thyroid dysfunction. This real-world thyroid function monitoring could aid in the management and early detection of thyroid dysfunction. In the thyroidology field, research involving the range of digital medicine technologies and their clinical applications is expected to be even more active in the future.

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Citations to this article as recorded by  

• An update on the safety of antithyroid drugs in pregnancy: the power of real-world data
  Stine Linding Andersen
  Expert Opinion on Drug Safety.2026; 25(3): 423.     CrossRef
• Precision Medicine in Autoimmune Thyroid Diseases: Decoding Biomarkers, Targeted Therapies and Digital Innovation
  Marcio José Concepción-Zavaleta, Jean Pierre Villanueva-De La Cruz, Jenyfer Fuentes Mendoza, Luis Concepción-Urteaga, Cristian D. Armas, Arturo Basurto-Ayala, José Paz-Ibarra
  Immunological Investigations.2026; 55(6): 1161.     CrossRef
• Thyroid function tests and resting heart rate in Graves’ disease: a prospective longitudinal study
  Beatrice Egger, Uwe Riedmann, Lisa Schmitt, Daniel Arian Kraus, Hannah Pichler, Christian Trummer, Verena Theiler-Schwetz, Stefanie Lindschinger, Winfried März, Oleksiy Tsybrovskyy, Markus Reichhartinger, Stefan Pilz
  Endocrine Connections.2026;[Epub]     CrossRef
• Cost-effectiveness Analysis Comparing Conventional and Digital Software Supported Management for Hypothyroidism
  Jung Hyun Kim, Jaeyong Shin, Man S Kim, Jae Hoon Moon
  The Journal of Clinical Endocrinology & Metabolism.2025; 110(6): 1596.     CrossRef
• Enhancing diagnostic accuracy of thyroid nodules: integrating self-learning and artificial intelligence in clinical training
  Daham Kim, Yoon-a Hwang, Youngsook Kim, Hye Sun Lee, Eunjung Lee, Hyunju Lee, Jung Hyun Yoon, Vivian Youngjean Park, Miribi Rho, Jiyoung Yoon, Si Eun Lee, Jin Young Kwak
  Endocrine.2025; 88(3): 766.     CrossRef
• Machine Learning for Thyroid Cancer Detection, Presence of Metastasis, and Recurrence Predictions—A Scoping Review
  Irina-Oana Lixandru-Petre, Alexandru Dima, Madalina Musat, Mihai Dascalu, Gratiela Gradisteanu Pircalabioru, Florina Silvia Iliescu, Ciprian Iliescu
  Cancers.2025; 17(8): 1308.     CrossRef
• Thyroid Cancer Staging: Historical Evolution and Analysis From Macrocarcinoma to Microcarcinoma
  Carlos S Duque, Carlos E Builes-Montaño, Catalina Tobón-Ospina, Alejandro Velez Hoyos, Juan G Sánchez, Andres F Londoño, Miguel Agudelo, Julio A Valencia, Juan P Dueñas, Maria F Palacio, Natalia Sierra
  Cureus.2025;[Epub]     CrossRef
• Clinical management of thyroid dysfunction in the aging population
  Bin Gao, Tongyan Yang, Guojuan Li
  Aging Research.2025; 3(3): 9340048.     CrossRef
• An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios
  Fuqiang Ma, Fengchang Yu, Xinyu Gu, Lihua Zhang, Zhilin Lu, Lele Zhang, Herong Mao, Nan Xiang
  BMC Endocrine Disorders.2025;[Epub]     CrossRef
• Understanding the factors of wearable devices among the patients with thyroid cancer: A modified UTAUT2 model
  LingLi Song, BinXian Li, HaiBo Wu, CuiCui Wu, XueQi Zhang, Zhiyuan Yu
  PLOS ONE.2024; 19(7): e0305944.     CrossRef
• The Current Progress of Artificial Intelligence in Approach to Thyroid Nodules: A Narrative Review
  Parsa Yazdanpanahi, Farnaz Atighi, Alireza Keshtkar, Reza Hamidi, Mohamadali Rezaeimanesh, Alireza Karimi, Arzhang Naseri, Mohammad Hossein Dabbaghmanesh
  Shiraz E-Medical Journal.2024;[Epub]     CrossRef
• AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions
  Yassine Habchi, Yassine Himeur, Hamza Kheddar, Abdelkrim Boukabou, Shadi Atalla, Ammar Chouchane, Abdelmalik Ouamane, Wathiq Mansoor
  Systems.2023; 11(10): 519.     CrossRef
• A COMPREHENSIVE INVESTIGATION INTO THE DEVELOPMENT OF A DEEP LEARNING MODEL FOR ROBUST CLASSIFICATION IN THYROID DISEASE DIAGNOSIS
  Minal Chaphekar, Omprakash Chandrakar
  ShodhKosh: Journal of Visual and Performing Arts.2023;[Epub]     CrossRef
• [Retracted] Empirical Method for Thyroid Disease Classification Using a Machine Learning Approach
  Tahir Alyas, Muhammad Hamid, Khalid Alissa, Tauqeer Faiz, Nadia Tabassum, Aqeel Ahmad, Gulnaz Afzal
  BioMed Research International.2022;[Epub]     CrossRef
• Deep Learning Based Classification of Wrist Cracks from X-ray Imaging
  Jahangir Jabbar, Muzammil Hussain, Hassaan Malik, Abdullah Gani, Ali Haider Khan, Muhammad Shiraz
  Computers, Materials & Continua.2022; 73(1): 1827.     CrossRef
• Diagnostic Performance of Kwak, EU, ACR, and Korean TIRADS as Well as ATA Guidelines for the Ultrasound Risk Stratification of Non-Autonomously Functioning Thyroid Nodules in a Region with Long History of Iodine Deficiency: A German Multicenter Trial
  Philipp Seifert, Simone Schenke, Michael Zimny, Alexander Stahl, Michael Grunert, Burkhard Klemenz, Martin Freesmeyer, Michael C. Kreissl, Ken Herrmann, Rainer Görges
  Cancers.2021; 13(17): 4467.     CrossRef
• Association between Thyroid Function and Heart Rate Monitored by Wearable Devices in Patients with Hypothyroidism
  Ki-Hun Kim, Juhui Lee, Chang Ho Ahn, Hyeong Won Yu, June Young Choi, Ho-Young Lee, Won Woo Lee, Jae Hoon Moon
  Endocrinology and Metabolism.2021; 36(5): 1121.     CrossRef
• Deep Learning based Classification of Thyroid Cancer using Different Medical Imaging Modalities : A Systematic Review
  Maheen Ilyas, Hassaan Malik, Muhammad Adnan, Umair Bashir, Wajahat Anwaar Bukhari, Muhammad Imran Ali Khan, Adnan Ahmad
  VFAST Transactions on Software Engineering.2021; 9(4): 1.     CrossRef
• Ultrasound risk stratification systems for thyroid nodule: between lights and shadows, we are moving towards a new era
  Pierpaolo Trimboli, Cosimo Durante
  Endocrine.2020; 69(1): 1.     CrossRef
• Associations of Thyroid Hormones and Resting Heart Rate in Patients Referred to Coronary Angiography
  Eva Steinberger, Stefan Pilz, Christian Trummer, Verena Theiler-Schwetz, Markus Reichhartinger, Thomas Benninger, Marlene Pandis, Oliver Malle, Martin H. Keppel, Nicolas Verheyen, Martin R. Grübler, Jakob Voelkl, Andreas Meinitzer, Winfried März
  Hormone and Metabolic Research.2020; 52(12): 850.     CrossRef