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From data to Diagnosis: How artificial intelligence is revolutionizing preoperative assessment of thyroid nodules and
Keyu Shen1, Meijuan Tan1, Yumeng Liu1
1Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People's Republic of China.
Background:
Thyroid nodules are frequently detected in the general population, raising concerns about the challenges of overdiagnosis and overtreatment. Artificial intelligence (AI) offers novel solutions for the preoperative evaluation of thyroid nodules. However, there has not yet been a comprehensive literature review on current applications.
Methods:
We reviewed the preoperative assessment methodologies for thyroid nodules and delineated the latest advancements in the utilization of sophisticated AI within the preoperative evaluation framework.
Results:
AI improves the accuracy of diagnostic procedures in preoperative evaluation of thyroid nodules by enhancing imaging, cytopathology diagnostics, and prognostic assessments. With its ability to automatically process large volumes of imaging and cytopathology data, AI minimizes reliance on clinical experience and reduces the occurrence of errors caused by subjective judgment. Furthermore, AI can integrate diverse data sources, providing a deeper understanding of the underlying value and interaction within the data, thereby enhancing comprehensive disease assessment and prognostic predictions.
Conclusion:
The AI-assisted preoperative assessment approach improves diagnostic accuracy and robust evidence for developing individualized treatment strategies.
