Artificial Intelligence (AI) is progressively permeating medicine, notably in the realm of
assisted diagnosis. However, the traditional unimodal AI models, reliant on large volumes of …

Because of technological advancements and their use in the medical area, many new
methods and strategies have been developed to address complex real-life challenges …

Colorectal cancer (CRC) is the third most common cause of cancer-related deaths. The five-
year relative survival rate for CRC is estimated to be approximately 90% for patients …

Objective To provide an overview of the decision fusion (DF) technique and describe the
applications of the technique in healthcare and medicine at prevention, diagnosis, treatment …

An effective multi-classifier fusion (MCF) system is demanding in the clinical context in terms
of integrating various diagnosis/prognosis predictive models to arrive at a stable and …

Accurate staging of liver fibrosis from magnetic resonance imaging (MRI) is crucial in clinical
practice. While conventional methods often focus on a specific sub-region, multi-view …

Objective Breast cancer (BC) is a multifactorial disease and is one of the most common
cancers globally. This study aimed to compare different machine learning (ML) techniques to …

Data harmonization is critical for establishing generalizable model on multicenter medical
data. Traditional data harmonization strategies aim to align data distributions from different …

Fusion of multimodal medical data provides multifaceted, disease-relevant information for
diagnosis or prognosis prediction modeling. Traditional fusion strategies such as feature …

Introduction: Recently, with the surge in the availability of relevant data in various industries,
the use of Information Fusion technique for data analysis is increasing. This method has …