Context: Recently, the machine learning (ML) field has been rapidly growing, mainly owing
to the availability of historical datasets and advanced computational power. This growth is …

Abstract Systems medicine (SM) has emerged as a powerful tool for studying the human
body at the systems level with the aim of improving our understanding, prevention and …

The Relief algorithm is a feature selection algorithm that uses the nearest neighbor to weight
attributes. However, Relief only considers the correlation between features, which leads to a …

In recent years, there have been many studies on the application and implementation of
machine learning techniques in the financial domain. Implementation of such state-of-the-art …

Recently, we have witnessed substantial success using the deep neural network in many
tasks. Although there still exist concerns about the explainability of decision making, it is …

Biomedical network learning offers fresh prospects for expediting drug repositioning.
However, traditional network architectures struggle to quantify the relationship between …

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary
field that considers the human body as a system, composed of multiple parts and of complex …

Detecting feature interactions is an important post-hoc method to explain black-box models.
The literature on feature interactions mainly focus on detecting their existence and …

Molecular property prediction is an important task in drug discovery, especially the
characterization of relationships between molecular substructures and their property. It is …

Analyzing historical decision-related data can help support actual operational decision-
making processes. Decision mining can be employed for such analysis. This paper …