The broad application of artificial intelligence techniques in medicine is currently hindered
by limited dataset availability for algorithm training and validation, due to the absence of …

Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Fast and reliable detection of patients with severe and heterogeneous illnesses is a major
goal of precision medicine,. Patients with leukaemia can be identified using machine …

Glioblastoma (GBM) is a particularly devastating tumor with a median survival of about 16
months. Recent research has revealed novel insights into the outstanding heterogeneity of …

Objectives To develop and test machine learning-based CT radiomics models for predicting
hospital stay in patients with pneumonia associated with SARS-CoV-2 infection. Design …

Recent advances in computer-aided diagnosis, treatment response and prognosis in
radiomics and deep learning challenge radiology with requirements for world-wide …

Background The coronavirus disease 2019 (COVID-19) has become a global challenge
since the December 2019. The hospital stay is one of the prognostic indicators, and its …

Objective To develop and validate a pretreatment magnetic resonance imaging (MRI)–
based radiomic-clinical model to assess the treatment response of whole-brain radiotherapy …

Simple Summary Following chemoradiation with alkylating agents in glioma patients,
structural magnetic resonance imaging (MRI) may suggest tumor progression which …

Simple Summary Radiomics and radiogenomics offer new insight into high-grade glioma
biology, as well as into glioma behavior in response to standard therapies. In this article, we …