AIMC Topic: Neural Networks, Computer

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Early prediction of sudden cardiac death using multimodal fusion of ECG Features extracted from Hilbert-Huang and wavelet transforms with explainable vision transformer and CNN models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Sudden cardiac death (SCD) is a critical health issue characterized by the sudden failure of heart function, often caused by ventricular fibrillation (VF). Early prediction of SCD is crucial to enable timely interventions. H...

AI driven interpretable deep learning based fetal health classification.

SLAS technology
In this study, a deep learning model is proposed for the classification of fetal health into 3 categories: Normal, suspect, and pathological. The primary objective is to utilize the power of deep learning to improve the efficiency and effectiveness o...

gGN: Representing the Gene Ontology as low-rank Gaussian distributions.

Computers in biology and medicine
Computational representations of knowledge graphs are critical for several tasks in bioinformatics, including large-scale graph analysis and gene function characterization. In this study, we introduce gGN, an unsupervised neural network for learning ...

Fusion of visible and fluorescence imaging through deep neural network for color value prediction of pelletized red peppers.

Journal of food science
A non-destructive method for determining the color value of pelletized red peppers is crucial for pepper processing factories. This study aimed to investigate the potentiality of visible and fluorescence images for the determination of color value of...

Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.

IEEE transactions on visualization and computer graphics
Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise...

Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction.

PloS one
INTRODUCTION: IVF is a widely-used assisted reproductive technology with a consistent success rate of around 30%, and improving this rate is crucial due to emotional, financial, and health-related implications for infertile couples. This study aimed ...

New approach for accurate discrimination and location of power transformers with different internal winding faults.

PloS one
Power transformers are essential elements in power systems and thus their protection schemes have critical importance. In this paper, a scheme is proposed for accurate discrimination and location of internal faults in power transformers using convent...

Colonoscopy polyp classification via enhanced scattering wavelet Convolutional Neural Network.

PloS one
Among the most common cancers, colorectal cancer (CRC) has a high death rate. The best way to screen for colorectal cancer (CRC) is with a colonoscopy, which has been shown to lower the risk of the disease. As a result, Computer-aided polyp classific...

Automated tumor localization and segmentation through hybrid neural network in head and neck cancer.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists
PURPOSE: Head and Neck (H&N) cancer accounts for 3% of cancer cases in the United States. Precise tumor segmentation in H&N is of utmost importance for treatment planning and administering personalized treatment dose. We aimed to develop an automatic...

Generation of a virtual cohort of TAVI patients for in silico trials: a statistical shape and machine learning analysis.

Medical & biological engineering & computing
PURPOSE: In silico trials using computational modeling and simulations can complement clinical trials to improve the time-to-market of complex cardiovascular devices in humans. This study aims to investigate the significance of synthetic data in deve...