There is a great discrepancy between the clinical categorization of MEFV gene variants and in silico tool predictions. In this study, we developed a seven-tier classification system for MEFV missense variants of unknown significance and recommended a...
Neutrophils, an essential innate immune cell type with a short lifespan, rely on continuous replenishment from bone marrow (BM) precursors. Although it is established that neutrophils are derived from the granulocyte-macrophage progenitor (GMP), the ...
Brain functional connectivity analysis is important for understanding brain development and brain disorders. Recent studies have suggested that the variations of functional connectivity among multiple subnetworks are closely related to the developmen...
Radiology report generation that aims to accurately describe medical findings for given images, is pivotal in contemporary computer-aided diagnosis. Recently, despite considerable progress, current radiology report generation models still struggled t...
Functional Magnetic Resonance Imaging (fMRI) is used for extracting blood oxygen signals from brain regions to map brain functional connectivity for brain disease prediction. Despite its effectiveness, fMRI has not been widely used: on the one hand, ...
Multiple instance learning (MIL) has emerged as a prominent paradigm for processing the whole slide image with pyramid structure and giga-pixel size in digital pathology. However, existing attention-based MIL methods are primarily trained on the imag...
Currently, machine learning applications in marketing allow to optimize strategies, personalize experiences and improve decision making. However, there are still several research gaps, so the objective is to examine the research trends in the use of ...
Revista da Associacao Medica Brasileira (1992)
Mar 17, 2025
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity classification.
In the realm of Wireless Sensor Networks (WSNs), the detection and mitigation of sinkhole attacks remain pivotal for ensuring network integrity and efficiency. This paper introduces SFlexCrypt, an innovative approach tailored to address these securit...
In response to the growing complexity of network threats, researchers are increasingly turning to machine learning and deep learning techniques to develop advanced models for malware detection. Many existing methods that utilize Application Programmi...
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