Collagen peptides are ubiquitously applied in food systems for their versatile bioactivities but face constraints from labor-intensive enzymatic screening and zoonotic risks from terrestrial sources. This study developed machine learning (ML) models ...
Soybean is being increasingly included in human diets, highlighting the importance of determining its composition. Although Fourier-Transform Near-Infrared Spectroscopy (FT-NIRS) has become a promising technology, currently used models remain limited...
Neurological Disorders (ND) affect a large portion of the global population, impacting the brain, spinal cord, and nerves. These disorders fall into categories such as NeuroDevelopmental (NDD), NeuroBiological (NBD), and NeuroDegenerative (ND) disord...
Identification of Alzheimer's Disease (AD), especially in its early phases, presents significant challenges due to the nonexistence of reliable biomarkers and effective treatments. Clinical trials for AD medications also suffer from high failure rate...
This paper comments on the valuable contribution by Carvalho and Gavaia regarding machine learning for osteoporosis risk prediction, particularly their use of a stacking ensemble model and feature importance analysis. While acknowledging the model's ...
BACKGROUND AND OBJECTIVE: Presence of spot sign on CT Angiography (CTA) is associated with hematoma growth in patients with intracerebral hemorrhage. Measuring spot sign volume over time may aid to predict hematoma expansion. Due to the difficulties ...
Breast cancer is the second leading cause of female mortality globally. Effective diagnostic tools, such as biosensors that utilize reliable biomarkers, are essential for early detection, particularly in low-income countries. This study introduces a ...
Peripheral artery disease (PAD) is a chronic condition caused by atherosclerosis, leading to arterial narrowing and obstruction, primarily in the lower extremities. This results in reduced blood flow and increases the risk of loss of limbs and mortal...
A crucial part of brain-computer interfaces is the use of electroencephalogram (EEG) signals for human emotion identification, which analyzes patterns of brain activity to determine the emotional state. This field of study is becoming increasingly im...
Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) to guide timely treatments. Traditional culture-based AST methods are slow, while existing whole-gen...
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