Reviews AI applications for improving diagnostic accuracy and management of bone tumors, suggesting future directions.
This paper reviews the research progress of artificial intelligence (AI) in bone tumor imaging and explores its potential applications in improving diagnostic accuracy and clinical management. Bone tumors, including primary and metastatic tumors, often face the risk of misdiagnosis due to their rarity and diverse imaging characteristics, which significantly impacts patient prognosis. AI technologies, particularly deep learning (DL) algorithms, have been widely applied to the automatic recognition and segmentation of bone tumor regions in images, enhancing the efficiency and accuracy of radiological image analysis. Furthermore, AI plays a crucial role in the classification of bone tumors and the assessment of treatment efficacy, providing support for the development of individualized treatment plans. With the continuous advancement of AI technology, future research should focus on expanding its applications across different types of bone tumors and integrating multimodal imaging data to further strengthen clinical decision-making and patient management.
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Zhang et al. (2026) studied this question.
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