Publications by authors named "Vekhova Ksenia Andreevna"
Artificial intelligence (AI) for tumor microenvironment (TME) and tumor budding (TB) identification in colorectal cancer (CRC) patients: A systematic review.
Olga Andreevna Lobanova Anastasia Olegovna Kolesnikova Valeria Aleksandrovna Ponomareva Ksenia Andreevna Vekhova Anaida Lusparonovna Shaginyan
J Pathol Inform
December 2024
Evaluation of the parameters such as tumor microenvironment (TME) and tumor budding (TB) is one of the most important steps in colorectal cancer (CRC) diagnosis and cancer development prognosis. In recent years, artificial intelligence (AI) has been successfully used to solve such problems. In this paper, we summarize the latest data on the use of artificial intelligence to predict tumor microenvironment and tumor budding in histological scans of patients with colorectal cancer.
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- Digital pathology enhances the field of diagnostics by allowing remote work for pathologists, improving diagnostic quality, and streamlining business processes, especially highlighted during the COVID-19 pandemic.
- The article shares insights from Russia's first fully digital pathomorphological laboratory, UNIM, covering various aspects such as technology use, economic benefits, and integration with laboratory information systems.
- Comprehensive analysis of statistical data and survey results on doctors' perspectives will be presented, showcasing the cost-effectiveness and competitiveness of the digital platform in the healthcare market.