Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …

The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …

Diabetes mellitus (DM) is a severe chronic disease that affects human health and has a high
prevalence worldwide. Research has shown that half of the diabetic people throughout the …

Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

Abstract Machine learning classifiers perform well on balanced datasets. Unfortunately, a lot
of the real-world data sets are naturally imbalanced. So, imbalanced classification is a …

Abstract Extracellular Vesicles (EVs), particularly exosomes, recently exploded into
nanomedicine as an emerging drug delivery approach due to their superior biocompatibility …

Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …

Artificial intelligence (AI) applications in oncology have been developed rapidly with
reported successes in recent years. This work aims to evaluate the performance of deep …

Background Oral cancer is a deadly disease among the most common malignant tumors
worldwide, and it has become an increasingly important public health problem in develo** …

Software Vulnerabilities (SVs) are increasing in complexity and scale, posing great security
risks to many software systems. Given the limited resources in practice, SV assessment and …