Accurate survival prediction is essential for precision oncology in patients with glioma.
However, current deep learning-based survival analysis methods highly rely on segmented …

Genomics allows the tracing of origin and evolution of cancer at molecular scale and
underpin modern cancer diagnosis and treatment systems. Yet, molecular biomarker …

Introduction This study addresses the lack of systematic investigation into the prognostic
value of hand‐crafted radiomic features derived from diffusion tensor imaging (DTI) in …

Background Optimizing patient selection for neoadjuvant chemotherapy in patients with
breast cancer remains an unmet clinical need. Quantitative features from medical imaging …

Accurate diagnose of Alzheimer's disease (AD), especially in its early stage, is very
important for the possible delay and early treatment of the disease. Many researches …

Deep learning (DL) is poised to redefine the way medical images are processed and
analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are …

The current work investigates the effect of humid conditions on the glass cover temperature
distribution of the parabolic trough solar collector system. For the aforementioned work, a …

Background To develop and validate a conventional MRI-based radiomic model for
predicting prognosis in patients with IDH wild-type glioblastoma (GBM) and reveal the …

Gliomas are highly heterogenous diseases with poor prognosis. Precise survival prediction
could benefit further clinical decision‐making, clinical trial incursion, and health economics …

Background Abnormal mitochondrial pyruvate carrier 1 (MPC1) expression plays a key role
in tumor metabolic reprogramming and progression. Understanding its significance in non …