While continuous glucose monitoring (CGM) has revolutionized metabolic health management, widespread adoption remains limited by cost constraints and usage burden, often resulting in interrupted monitoring periods. We propose a deep learning framewor...
Restless legs syndrome (RLS) is a relatively common neurosensory disorder that causes an irresistible urge for leg movement. RLS causes sleep disturbances and reduced quality of life, but accurate diagnosis remains challenging owing to the reliance o...
Advanced high strength steels (AHSS) exhibit diverse mechanical properties due to their complex chemical compositions and microstructures. Existing machine learning (ML) studies often focus on specific steel grades, limiting generalizability in predi...
Naturally derived carbon quantum dots (CQDs) are novel carbon-based nanomaterials with excellent traits. It is highly demanded to develop CQDs from biowaste that have excellent photostability, a simple synthesis approach, and an appealing output so t...
Wildlife biologists increasingly use camera traps for monitoring animal populations. However, manually sifting through the collected images is expensive and time-consuming. Current deep learning studies for camera trap images do not adequately tackle...
Regardless of the materials' intrinsic characteristics, electrochemical discharge drilling (ECDD) effectively micro-machines various materials. The present article optimizes the ultrasonic assisted rotary ECDD (UR-ECDD) process for maximizing the mat...
The accurate preoperative staging of laryngeal squamous cell carcinoma (LSCC) provides valuable guidance for clinical decision-making. The objective of this study was to establish a multiparametric MRI model using radiomics and deep learning (DL) to ...
High-content screening (HCS) for bioimaging is a powerful approach to studying biological processes, enabling the acquisition of large amounts of images from biological samples. However, it generates massive amounts of metadata, making HCS experiment...
This study examines how imbalanced datasets affect the accuracy of machine learning models, especially in predictive analytics applications such as churn prediction. When datasets are skewed towards the majority class, it can lead to biased model per...
Medical interns are at high risk of acquiring Hepatitis B Virus (HBV) infection during their training. HBV vaccination is the most effective measure to reduce the global incidence of HBV. The duration of protection after HBV vaccination is still cont...
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