Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk...
The object of this study was to assess the similarities and differences of radiomics features on full field digital mammography (FFDM) in FOR PROCESSING and...
The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of...
In this educational review, the authors take a comprehensive look at various aspects and applications of artificial intelligence (AI) in the field of...
The authors of this study conducted multiparametric magnetic resonance imaging (MRI)-derived radiomics based on multi-scale tumor region in order to predict...
Radiomics studies often perform a feature selection step to remove redundant and irrelevant features from the generic features extracted from radiological...
The authors of this study aimed to systematically review radiomic feature reproducibility and predictive model validation strategies in studies that deal with...
The authors of this retrospective study aimed to evaluate the diagnostic performance of a radiomics model in order to classify hepatic cyst, hemangioma, and...
The idea of quantification of disease severity of chronic obstructive pulmonary disease (COPD) with CT has been introduced as early as the late 1980s with the...
Radiomics as a research topic in radiology is certainly a promising field. Over the last years, many publications have shown promising results, showing that...
Welcome to the blog on Artificial Intelligence of the European Society of Radiology
This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.
