One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of false negative diagnoses challenges in hospitals. The aim of this paper is to propose and develop a ...
Biomedical physics & engineering express
Jan 21, 2025
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...
. Developing an efficient and generalizable method for inter-subject emotion recognition from neural signals is an emerging and challenging problem in affective computing. In particular, human subjects usually have heterogeneous neural signal charact...
Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central ne...
OBJECTIVE: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small bowel obstruction (ASBO) in infants under 3 months with intestinal malrotation.
AIM: In this research, we leveraged bioinformatics and machine learning to pinpoint key risk genes associated with occupational benzene exposure and to construct genomic and algorithm-based predictive risk assessment models.
Adenosine receptors (A, A, A, A) play critical roles in cellular signaling and are implicated in various physiological and pathological processes, including inflammations and cancer. The main aim of this research was to investigate structure-activity...
International journal of occupational safety and ergonomics : JOSE
Jan 20, 2025
This study attempted to optimize the adaptive neuro-fuzzy inference system (ANFIS) using particle swarm optimization (PSO) and a genetic algorithm (GA) for calculating occupational risk. Numerous studies have shown that the ANFIS is a good approach f...
Neural networks : the official journal of the International Neural Network Society
Jan 20, 2025
Anomaly detection on graph data has garnered significant interest from both the academia and industry. In recent years, fueled by the rapid development of Graph Neural Networks (GNNs), various GNNs-based anomaly detection methods have been proposed a...
Medical & biological engineering & computing
Jan 20, 2025
Source-free domain adaptation (SFDA) has become crucial in medical image analysis, enabling the adaptation of source models across diverse datasets without labeled target domain images. Self-training, a popular SFDA approach, iteratively refines self...
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