Gastric cancer and Colon adenocarcinoma represent widespread and challenging
malignancies with high mortality rates and complex treatment landscapes. In response to the …

Stroke prediction plays a crucial role in preventing and managing this debilitating condition.
In this study, we address the challenge of stroke prediction using a comprehensive dataset …

With the fast growth of web, the web is full of diverse data. Linked Data is data on the web
that gives URIs to entities and links different data from different domains together, which …

In recent years, methods founded on deep learning have exhibited notable efficacy within
the field of medical image denoising. However, the majority of deep learning approaches …

Portion of the causes of medical errors in outpatient clinics are incorrect treatment resulting
from misdiagnosis. Misdiagnosis between diseases is often caused by similar and …

The fairness issue of clinical data modeling, especially on Electronic Health Records
(EHRs), is of utmost importance due to EHR's complex latent structure and potential …

The right to be forgotten (RTBF) seeks to safeguard individuals from the enduring effects of
their historical actions by implementing machine-learning techniques. These techniques …

To enhance the quality of medical services, Machine Learning (ML) techniques have been
widely applied to model Electronic Health Records (EHRs). Nevertheless, clinical data …

Abstract Machine learning and Reinforcement Learning (RL) have received a lot of
attentions in decision making problems. For individualized decision making, due to possible …

The magnetically controlled capsule endoscopy (MCCE) is an emerging modality for
assessing gastrointestinal disorders due to its advantages. However, current assignments of …