OBJECTIVES: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Certain genes have been identified as important clinical risk factors for AD, and technological advances in gen...
Computational intelligence and neuroscience
Jul 14, 2021
In high-paced and efficient life and work, fatigue is one of the important factors that cause accidents such as traffic and medical accidents. This study designs a feature map-based pruning strategy (PFM), which effectively reduces redundant paramete...
BACKGROUND AND OBJECTIVE: Clinical characteristics of obesity are heterogenous, but current classification for diagnosis is simply based on BMI or metabolic healthiness. The purpose of this study was to use machine learning to explore a more precise ...
INTRODUCTION: Approximately 7,000 newborns die every day, accounting for almost half of child deaths under 5 years of age. Deciphering which neonates are at increased risk for mortality can have an important global impact. As such, integrating high c...
Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to mis...
Supplier selection is an important decision-making problem, which involves many quantitative and qualitative factors incorporating vagueness and imprecision. This study proposes a novel fuzzy multi-criteria decision-making framework for supplier sele...
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients fr...
While laser ablation has become an increasingly important tool in the neurosurgical oncologist's armamentarium, deep seated lesions, and those located near critical structures require utmost accuracy during stereotactic laser catheter placement. Robo...
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...
OBJECTIVE: To develop and validate a convolutional neural network (CNN) capable of predicting the anatomical landmarks used to calculate the hip-knee-ankle angles (HKAAs) from radiographs and thereby quantify lower extremity alignments in children.
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