Recent advances in MRI‐guided radiation therapy (MRgRT) and deep learning techniques
encourage fully adaptive radiation therapy (ART), real‐time MRI monitoring, and the MRI …

Introduction: Accurate diagnosis is crucial for brain tumors, given their low survival rates and
high treatment costs. However, traditional methods relying on manual interpretation of …

Background MRI radiomic features and machine learning have been used to predict brain
metastasis (BM) stereotactic radiosurgery (SRS) outcomes. Previous studies used only …

Qualitative observer-based and quantitative radiomics-based analyses of T1w contrast-
enhanced magnetic resonance imaging (T1w-CE MRI) have both been shown to predict the …

In this paper, we study the role of predictive artificial intelligence (AI) in human
decisionmaking. Using a rich decision-level data set from the maintenance of heavy-duty …

Brain tumors can develop when abnormal cells in the brain grow uncontrollably, and MRI
images provide valuable information about the presence of unwanted tissue growth …

Background and purpose: Timely identification of Local Failure (LF) after stereotactic
radiosurgery offers the opportunity for appropriate treatment modifications that may result in …

Advancements in deep learning (DL) techniques have brought a ray of hope in the battle
against brain tumors by significantly improving their detection and segmentation in MRI …

Background and purpose Timely identification of local failure after stereotactic radiotherapy
for brain metastases allows for treatment modifications, potentially improving outcomes …