Study Results from Hong Kong Polytechnic University Broaden Understanding of Diagnostics (Enhancing the Clinical Utility of Radiomics: Addressing the Challenges of Repeatability and Reproducibility in CT and MRI).

Předmět:	MACHINE learning REPORTERS & reporting MEDICAL informatics FEATURE selection RADIOMICS
Zdroj:	Health & Medicine Week; 9/13/2024, p7832-7832, 1p
Abstrakt:	A recent study conducted by researchers at Hong Kong Polytechnic University explores the challenges of repeatability and reproducibility in radiomics, a field that combines imaging phenotypes with machine learning algorithms for the diagnosis and prognosis of oncological conditions. The study emphasizes the need to address these challenges in order to facilitate the successful translation of radiomic models from research to clinical practice. The researchers suggest four recommendations for repeatability and reproducibility studies, including detailed reporting of variation sources and transparent disclosure of calculation parameters. This research contributes to a better understanding of the factors that influence the reliability of radiomic features in CT and MRI scans. [Extracted from the article]
Databáze:	Complementary Index
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