Machine Learning Approach for Differentiation of Pheochromocytoma from Adrenocortical Cancer and Non-Functioning Adrenal Adenomas
We developed robust ML models capable of accurately differentiating PCC from other adrenal tumors in complex cases. The models provide a clinically actionable tool for pre-surgical decision support. Furthermore, the identification of key discriminative features enhances the clinical understanding of PCC and facilitates its differential diagnosis prior to histological verification.
Authors
- Irena Ilovayskaya (ORCID: https://orcid.org/0000-0003-3261-7366)
- A. Yu. Lugovskaya (ORCID: https://orcid.org/0000-0002-5187-1602)
- Lidia N. Nefedova (ORCID: https://orcid.org/0000-0002-6192-6507)
- Timur Nurkhabinov (ORCID: https://orcid.org/0009-0009-5702-3899)
- Victor Popov
Institutions
- Lomonosov Moscow State University (RU)
- Moscow Regional Scientific Research Clinical Institute. MF Vladimirsky (RU)
- Regional Clinical Research (US)
- Moscow State University (TJ)
Publication Details
- Journal
- Life
- Published
- 2026-01-19
- DOI
- https://doi.org/10.3390/life16010164
- Primary Topic
- Adrenal and Paraganglionic Tumors
- Type
- article
- Field-Weighted Citation Impact
- 0.00