The Role of Artificial Intelligence in Personalized Targeted Therapy of Thyroid Cancer: An Emerging Frontier

Thyroid cancer is the most common malignancy of the endocrine system and has shown a rapidly increasing incidence rate in recent decades worldwide. The introduction of targeted therapies has significantly revolutionized treatment outcomes in patients with advanced or metastatic thyroid cancer. Despite this, challenges remain in finding the best therapies for a particular patient and monitoring response to treatment. Artificial intelligence (AI) provides a promising way to overcome these shortfalls through various data analysis, pattern recognition, and predictive modeling capabilities. Method:This study was performed using the collected article in English that was available on details of the main topic from ۲۰۰۰ to ۲۰۲۱ in Scopus, PubMed, and Web of Science with keywords breast cancers, TNBC, targeted therapy, EGFR receptor, and RTK receptor. Articles were selected based on the exclusion criteria a and, after reviewing, were included in the study. Rsults:AI has great potential to revolutionize personalized, targeted therapy in thyroid cancer through several vital applications that include enhanced diagnosis and prognosis. AI algorithms would interpret voluminous datasets of medical images, genomics, and clinical information for improved diagnostic accuracy in identifying high-risk patients and treatment outcomes. Personalized Selection of Treatment: AI can integrate multi-omics data of a patient to help decide on the best-targeted therapies for each patient with his/her specific tumor and molecular characteristics. Real-time Monitoring of Treatment Responses: AI-driven software can continuously monitor treatment responses and detect early signs of resistance to the therapeutic agent in use, thus enabling the correct timing of change in therapy and mitigation of any adverse effects. AI may accelerate the identification, discovery, and development of new targeted therapies through drug target identification, drug efficacy prediction, or clinical trial design optimization. Although AI has great promise for personalized, targeted thyroid cancer therapy, substantial challenges must be overcome before it can become a practical reality. The latter include data quality and availability; therefore, access to large, various high-quality datasets is considered indispensable for the training and validation of AI algorithms. Collaboration between researchers, clinicians, and data scientists is critical to ensure data availability and quality.Interpretability of Algorithms; Many AI algorithms are "black boxes," making it usually impossible to understand how the algorithm arrived at its prediction. Developing more interpretable models will be significant in building trust and ethical use in clinical practice. Regulation and Ethics; The use of AI in clinical decision-making begets severe regulatory and ethical questions, including those touching on data privacy, bias in algorithms, and issues of liability.These must be sorted out for AI's responsible and equitable application in health. Conclusion: AI will profoundly affect personalized, targeted therapy for thyroid cancer. By capitalizing on AI's power, we will improve patient outcomes, optimize treatment choices, and accelerate the development of new therapies. Some key challenges that remain to be overcome if AI is to be used effectively in a clinical setting are data, interpretability, and ethics. With continued research and development, AI has great potential to revolutionize how we treat thyroid cancer, making it increasingly more precise and personalized, thus benefiting the patients.

کلیدواژه ها:

Artificial Intelligence ، Personalized Medicine ، Targeted Therapy ، Thyroid Cancer