In recent years, the surge in glioma brain tumor cases has positioned it as the 10th most
prevalent tumor affecting individuals across diverse age groups. Gliomas, characterized by …

Histopathological whole slide images (WSIs) are the gold standard for cancer diagnosis. In
prognosis, WSIs can also help predict the overall survival (OS) time of cancer (such as …

Survival prediction is crucial for cancer patients as it provides early prognostic information
for treatment planning. Recently, deep survival models based on deep learning and medical …

Early survival prediction is vital for the clinical management of cancer patients, as tumors
can be better controlled with personalized treatment planning. Traditional survival prediction …

Previous efforts in vision community are mostly made on learning good representations from
visual patterns. Beyond this, this paper emphasizes the high-level ability of causal …

Prognostic risk prediction is pivotal for clinicians to appraise the patient's esophageal
squamous cell cancer (ESCC) progression status precisely and tailor individualized therapy …

Purpose In computer-aided diagnosis, the fusion of image features extracted from neural
networks and clinical information is crucial to improve diagnostic accuracy. How to integrate …

Objective: Glioblastoma multiforme (GBM), particularly the IDH-wildtype type, represents a
significant clinical challenge due to its aggressive nature and poor prognosis. Despite …

Survival prediction is a major concern for cancer management. Deep survival models based
on deep learning have been widely adopted to perform end-to-end survival prediction from …

Acute ischemic stroke (AIS) is a cerebrovascular disease caused by deceased blood flow in
the brain. Treatment of AIS is heavily dependent on the time since stroke onset (TSS), either …