Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …

Background To evaluate radiomics analysis in neuro-oncologic studies according to a
radiomics quality score (RQS) system to find room for improvement in clinical use. Methods …

Gliomas can be classified into five molecular groups based on the status of IDH mutation,
1p/19q codeletion, and TERT promoter mutation, whereas they need to be obtained by …

Radiomics-based researches have shown predictive abilities with machine-learning
approaches. However, it is still unknown whether different radiomics strategies affect the …

Independent component analysis (ICA) is a matrix factorization approach where the signals
captured by each individual matrix factors are optimized to become as mutually independent …

Background Prediction of brain invasion pre-operatively rather than postoperatively would
contribute to the selection of surgical techniques, predicting meningioma grading and …

Thyroid nodules have a high prevalence and a small percentage is malignant. Many non-
invasive methods have been developed with the help of the Internet of Things to improve the …

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …

We aimed to develop and validate a multiparametric MR radiomics model using
conventional, diffusion-, and perfusion-weighted MR imaging for better prognostication in …

Background High‐and low‐risk endometrial cancer (EC) differ in whether lymphadenectomy
is performed. Assessment of high‐risk EC is essential for planning surgery appropriately …