With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Gastric cancer is the high mortality rate cancers globally, and the current survival rate is 30%
even with the use of combination therapies. Recently, mounting evidence indicates the …

Background: With an increase in the number of artificial intelligence (AI) and machine
learning (ML) algorithms available for clinical settings, appropriate model updating and …

Breast cancer is a significant global health concern, with millions of cases and deaths each
year. Accurate diagnosis is critical for timely treatment and medication. Machine learning …

The accuracy of machine learning methods is often limited by the amount of training data
that is available. We proposed to improve machine learning training regimes by augmenting …

The advent of high-throughput omics technologies has led to the generation of a large
volume of omics data to be analyzed. Individual analyses of omics layers provide only a one …

This paper argues for the importance of detailed reporting of results of machine learning
modeling applied in medical, healthcare and health applications. It describes ten criteria …

Glioblastoma multiforme (GBM) is the most aggressive brain cancer in adults, with 3.2–3.4
cases per 100 thousand. In the US, brain cancer does not rank in the top 10 causes of death …

Background In this era of data science-driven bioinformatics, machine learning research has
focused on feature selection as users want more interpretation and post-hoc analyses for …

Bone tumor is a kind of rare cancer, the location of which is mainly in bone tissue as well as
cartilage tissue. Bone tumor is mainly classified into benign and malignant types. The …