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DOI 10.3390/jimaging12030138

Медицинская библиотека · Journal of imaging · 2026

Current Trends and Future Prospects of Radiomics and Machine Learning (ML) Models in Spinal Tumors-A Narrative Review.

Sanker Vivek, Panchawgh Suhrud, Kaur Anmol, Suresh Vinay, Mahesh Dhanya, Ahmad Eeman, Hariharan Srinath, Pangal Dhiraj, Cavgnaro Maria Jose, Rusu Mirabela, Ratliff John, Desai Atman

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Аннотация

The intersection between radiomics, the computational analysis of imaging data, and machine learning (ML) may lead to new developments in the diagnosis, prognosis, and management of diseases. For spinal tumors specifically, applications of these fields appear promising. In this educational narrative review, we provide a summary of the current advancements in radiomics and artificial intelligence (AI), as well as applications of both fields in the diagnosis and management of spinal tumors. We also provide a suggested workflow of radiomics and machine learning analysis of spinal tumors for researchers, including a list and description of commonly used radiomic features. Future directions in the field of radiomics and machine learning applications to spinal tumors may involve validating already proposed algorithms with larger datasets, ensuring that all computational applications to patient care maintain high ethical standards, and continuing work in developing novel and highly accurate computational techniques to enhance patient outcomes.

Для цитирования: Sanker Vivek, Panchawgh Suhrud, Kaur Anmol, Suresh Vinay, Mahesh Dhanya, Ahmad Eeman, Hariharan Srinath, Pangal Dhiraj, Cavgnaro Maria Jose, Rusu Mirabela, Ratliff John, Desai Atman. Current Trends and Future Prospects of Radiomics and Machine Learning (ML) Models in Spinal Tumors-A Narrative Review.. Journal of imaging. 2026. DOI: 10.3390/jimaging12030138.
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