In the medical domain, the challenges in sample acquisition and collection often result in imbalanced training sets for multi-class models, especially in disease subtype differentiation. We propose a novel method to address multi-class imbalance in s...
BACKGROUND: Infection by the SARS-CoV-2 virus can cause coronavirus disease 2019 (COVID-19) and can also exacerbate the symptoms of Kawasaki disease (KD), an acute vasculitis that mostly affects children. This study used bioinformatics and machine le...
Machine learning (ML) is increasingly valuable for predicting molecular properties and toxicity in drug discovery. However, toxicity-related end points have always been challenging to evaluate experimentally with respect to translation due to the re...
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....
When applying machine learning (ML) approaches for the prediction of bioactivity, it is common to collect data from different assays or sources and combine them into single data sets. However, depending on the data domains and sources from which thes...
Over the past 60 years, drug-induced liver injury (DILI) has played a key role in the withdrawal of marketed drugs due to safety concerns. Early prediction of DILI is crucial for developing safer pharmaceuticals, yet current and testing methods are...
Waste classification is a critical step in waste management that is time-consuming and necessitates automation to replace traditional approaches. Recently, machine learning (ML) and deep learning (DL) have gained attention from researchers seeking to...
Federated learning is widely used for collaborative training of human activity recognition models across multiple devices with limited local data. However, label noise caused by human and time constraints during data annotation is common and severely...
Understanding the molecular underpinnings of CAD is essential for developing effective therapeutic strategies. This study aims to identify and analyze differentially expressed hub biomarkers in the peripheral blood of CAD patients. Based on RNA-seq d...
BACKGROUND: Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are on the rise. While there is evidence of a link between the two diseases, the pathophysiological mechanisms they share are not fully understood.
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