| For: | Nagendra L, Pappachan JM, Fernandez CJ. Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions. Artif Intell Cancer 2023; 4(1): 1-10 [DOI: 10.35713/aic.v4.i1.1] |
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| URL: | https://www.wjgnet.com/2644-3228/full/v4/i1/1.htm |
| Number | Citing Articles |
| 1 |
Matthew A. Penner, Derek Berger, Xuchen Guo, Jacob Levman. Machine Learning in Differentiated Thyroid Cancer Recurrence and Risk Prediction. Applied Sciences 2025; 15(17): 9397 doi: 10.3390/app15179397
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| 2 |
Yanche Ari Kustiawan, Khairil Imran Ghauth, Sakina Ghauth, Liew Yew Toong, Sien Hui Tan. Artificial Intelligence Techniques for Thyroid Cancer Classification: A Systematic Review. Machine Learning and Knowledge Extraction 2026; 8(2): 27 doi: 10.3390/make8020027
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| 3 |
Heram Cho, Yunseo Park, Seung-Kwon Myung. Physical activity and risk of thyroid cancer: a systematic review and meta-analysis of prospective cohort studies. International Journal of Clinical Oncology 2025; 30(12): 2512 doi: 10.1007/s10147-025-02907-x
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| 4 |
Mohanad A. Deif, Iman Akour, Mohamed Elhoseny. Optimizing thyroid cancer recurrence prediction using tribal intelligent evolution and XGBoost: Toward enhanced clinical decision support. Informatics in Medicine Unlocked 2025; 59: 101702 doi: 10.1016/j.imu.2025.101702
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| 5 |
Alyssa Kuang, Valentina L. Kouznetsova, Santosh Kesari, Igor F. Tsigelny. Diagnostics of Thyroid Cancer Using Machine Learning and Metabolomics. Metabolites 2023; 14(1): 11 doi: 10.3390/metabo14010011
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| 6 |
Deepak Thakur, Tanya Gera, Vivek Bhardwaj, R. Mazen, Ayodele Lasisi, Trmesgen Engida. A comparative study on advanced predictive modeling of thyroid cancer recurrence using multi algorithmic machine learning frameworks. Scientific Reports 2025; 16(1) doi: 10.1038/s41598-025-33396-7
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| 7 |
Qaviullah Mian, Nebiyou Bayleyegn. Recent Advances in Thyroid Disorders. 2025; doi: 10.5772/intechopen.1010909
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| 8 |
Saleh Ateeq Almutairi. Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images. PeerJ Computer Science 2025; 11: e3063 doi: 10.7717/peerj-cs.3063
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| 9 |
Junseok Kang, Jihyun Ahn, Jeong Hun Hah. Artificial Intelligence for Thyroid Ultrasound: Clinical Performance, Pitfalls, and Practice Integration. Clinical Ultrasound 2025; 10(2): 59 doi: 10.18525/cu.2025.10.2.59
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| 10 |
I.A. Solovev. Artificial intelligence in pathological anatomy. Russian Journal of Archive of Pathology 2024; 86(2): 65 doi: 10.17116/patol20248602165
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| 11 |
Bassam Abdul Rasool Hassan, Ali Haider Mohammed, Souheil Hallit, Diana Malaeb, Hassan Hosseini. Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook. Frontiers in Oncology 2025; 15 doi: 10.3389/fonc.2025.1475893
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| 12 |
Qiang Deng, Xiaoping Men, Duo Jin, Yuzhuo Bai. Integrating Robotic Bilateral Axillo-Breast Approach Thyroidectomy with Molecular Diagnostics and Artificial Intelligence in Thyroid Cancer Care. Biomolecules & Therapeutics 2026; 34(1): 45 doi: 10.4062/biomolther.2025.125
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| 13 |
Na Han, Rui Miao, Dongwei Chen, Jinrui Fan, Lin Chen, Siyao Yue, Tao Tan, Bowen Yang, Yapeng Wang. An Early Thyroid Screening Model Based on Transformer and Secondary Transfer Learning for Chest and Thyroid CT Images. Technology in Cancer Research & Treatment 2025; 24 doi: 10.1177/15330338251323168
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| 14 |
Shanu Verma, Rashmi Popli, Harish Kumar, Brijesh Kumar Chaurasia. AI leveraging solution for thyroid disease: advances and rationale. Network Modeling Analysis in Health Informatics and Bioinformatics 2025; 14(1) doi: 10.1007/s13721-025-00592-4
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| 15 |
Elizabeth Clark, Samantha Price, Theresa Lucena, Bailey Haberlein, Abdullah Wahbeh, Raed Seetan. Predictive Analytics for Thyroid Cancer Recurrence: A Machine Learning Approach. Knowledge 2024; 4(4): 557 doi: 10.3390/knowledge4040029
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