AIMC Topic: Neural Networks, Computer

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Enhancing explainability in ECG analysis through evidence-based AI interpretability.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While pre-trained neural networks, e.g., for diagnosis from electrocardiograms (ECGs), are already available and show remarkable performance, their lack of transparency prevents translation to clinical practice. Recently, an explainable artificial in...

Leveraging Deep Learning Model for Computer Vision-Based Brain Tumor Classification in 3D MRI Brain Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study uses computer vision techniques to combine EfficientNet-3D and 3D Residual neural network(3DResnet) deep learning architecture to detect brain tumours in magnetic resonance imaging (MRI). The dataset includes a collection of 586 sets of br...

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a pre-trained Convolutional Neural Network (CNN) classifier as its backbone. Deviating from traditional architectures with a symmetric U-shape, EffiSegN...

PhysioSens1D-NET: A 1D Convolution Network for Extracting Heart Rate from Facial Videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Non-contact heart rate (HR) monitoring from video streams is the most established approach to unobtrusive vitals monitoring. A multitude of classical signal processing algorithms and cutting-edge deep learning models have been developed for non-conta...

Clinical Assessment of a Lightweight CNN Model for Real-Time Atrial Fibrillation Prediction in Continuous Wearable Monitoring.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial risk for affected individuals. The integration of wearable devices, coupled with advanced predictive models, opens pathways for non-invasive and real-tim...

Personality Trait Recognition using ECG Spectrograms and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals. The research explores the potential of ECG-derived spectrograms as informative features in detec...

Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constraine...

Visual In-Context Learning for Few-Shot Eczema Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automated diagnosis of eczema from digital camera images is crucial for applications that allow patients to self-monitor their recovery. An important component of this is the segmentation of eczema region from such images. Current methods for eczema ...

Interpretable SincNet-Based Spatiotemporal Neural Network for Seizure Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Spatiotemporal convolutional neural networks (CNNs) have emerged as potent tools for seizure prediction (SP) using electroencephalogram (EEG) signals, probing spatiotemporal biomarkers in epileptic brains. Nevertheless, it poses significant challenge...

Channel Fitting Network for Retinal Lesion Segmentation from OCT Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Retinal lesion is a cause of age-related macular degeneration that poses a big threat to elderly population. The accurate detection and segmentation of retinal lesions benefits the early diagnosis of age-related macular degeneration and monitoring of...