AIMC Topic: Neural Networks, Computer

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Dynamic multi-hypergraph structure learning for disease diagnosis on multimodal data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
With its superior capability in complex data modeling, hypergraph computation is a powerful tool for many applications. In this work, we propose using hypergraph computation for disease prediction. Hypergraphs allow for the representation of higher-o...
Diagnosis, Computer-Assisted Cluster Analysis Machine Learning Algorithms Alzheimer Disease Humans Autism Spectrum Disorder Neural Networks, Computer
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CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Imaging data collected from different sites is difficult to pool together due to unwarranted variations introduced by different acquisition protocols or scanners. Data harmonization is an effective way to mitigate site-specific bias while preserving ...
Magnetic Resonance Imaging Supervised Machine Learning Neuroimaging Algorithms Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Geno-GCN: A Genome-specific Graph Convolutional Network for Diabetes Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Drawing inspiration from convolutional neural networks, graph convolutional networks (GCNs) have been implemented in various applications. Yet, the integration of GCNs into clinical settings, particularly in the context of complex health conditions l...
Genome, Human Genomics Machine Learning Computational Biology Algorithms Humans Neural Networks, Computer Diabetes Mellitus, Type 2
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Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model training. Synthetic data plays a pivotal role in mitigating challenges ...
Machine Learning Algorithms Dermoscopy Image Processing, Computer-Assisted Skin Neoplasms Diffusion Humans Skin Diseases Neural Networks, Computer
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Heart Rate Estimation from Neck Photoplethysmography using FFT-Based Scoring and a Shallow Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Heart rate (HR) is one of the most important vital signs to monitor. Constantly monitoring HR makes it important to have an easy-to-use system that is able to achieve clinically acceptable measurement accuracy. Depending on the monitoring device's ul...
Signal Processing, Computer-Assisted Heart Rate Female Adult Humans Photoplethysmography Neural Networks, Computer Male Neck Algorithms
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Deep Learning-Based Subject Independent Human Activity Recognition using Smart Lacelock Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Human Activity Recognition (HAR) field is rapidly growing and the classification of human activities based on sensor data is crucial for applications in healthcare, rehabilitation and numerous other sectors. In this paper we use a novel device and at...
Deep Learning Wearable Electronic Devices Human Activities Shoes Accelerometry Humans Neural Networks, Computer Algorithms
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Predicting Hemodynamic and Pulmonary Decompensation with Deep Neural Networks: Performance and Explainability.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Predicting the deterioration of patients' hemodynamic and pulmonary decompensation state while being treated on an intensive care unit is demanding for the medical staff involved. Recent developments in artificial intelligence (AI) show the potential...
Artificial Intelligence Hemodynamics Deep Learning Humans Neural Networks, Computer
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Arterial Diameter Trend Estimation Using Deep Learning on Ultrasound Spectral Doppler.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
This study presents an approach for estimating gaps in arterial diameter using flow velocity obtained from spectral Doppler data. We utilize short-time Fourier transform in conjunction with deep learning models designed for spectrograms to estimate a...
Algorithms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Arteries Ultrasonography, Doppler Fourier Analysis
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Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
As the COVID-19 pandemic has put a strain on healthcare systems around the world, accurate and rapid virus detection has become increasingly important. Lung issues caused by COVID-19 can be detected using a chest X-ray (CXR). In order to automaticall...
Radiography, Thoracic Convolutional Neural Networks Support Vector Machine COVID-19 Algorithms Lung Humans Deep Learning Neural Networks, Computer SARS-CoV-2
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LightIED: Explainable AI with Light CNN for Interictal Epileptiform Discharge Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Interictal epileptic discharge (IED) detection from electroencephalography (EEG) is an important but difficult step in the epilepsy diagnosis. To reduce the workload of doctors, some diagnostic auxiliary methods based on deep learning have been propo...
Humans Neural Networks, Computer Electroencephalography Epilepsy Algorithms Machine Learning Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted
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