AIMC Topic: Algorithms

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Hybrid deep learning framework for cardiovascular disease diagnosis and prognosis using GAN, LSTM, GRU, VARMA, and deep DynaQ network.

Scientific reports
Cardiovascular diseases (CVDs) are a major cause of morbidity and mortality worldwide. Effective CVD treatment requires early and accurate diagnosis. CVD diagnosis and prognosis can be done using medical image analysis. In this paper, we propose a no...

Using convolutional neural networks with late fusion to predict heart disease.

Scientific reports
Cardiovascular diseases are responsible for one-third of all deaths that occur globally. Machine learning and data mining have made it easier and quicker for physicians to diagnose or identify patients. This article presents a novel late fusion metho...

Enhancing cardiac disease prediction with explainable bidirectional LSTM.

Scientific reports
Cardiovascular disorders (heart diseases) are the most prevalent cause of death on a global scale. So early detection and classification increase the likelihood of survival. In the context of machine learning techniques, there is always a need for an...

Evaluation of deep learning-based retinal pigment epithelium segmentation for a widely used optical coherence tomography device.

Scientific reports
To develop our proposed technology method to improve retinal pigment epithelium (RPE) detection in optical coherence tomography (OCT) images and compare its efficacy with Topcon's automated segmentation algorithm across multiple retinal diseases and ...

A multi-head YOLOv12 with self-supervised pretraining for urinary sediment particle detection.

Scientific reports
Automatic and reliable urine sediment analysis is essential for timely diagnosis and management of renal and urinary disorders. However, manual methods are time-consuming, subjective, and limited by operator abilities. In this study, we propose a nov...

Conditional diffusion model for high-accuracy brain tumor segmentation in MRI images.

Scientific reports
The segmentation accuracy of deep learning-based brain tumor MRI images still requires further improvement. We proposed a conditional diffusion network that incorporates image information into the mask's perturbed diffusion process. By optimizing the...

An enhanced social emotional recognition model using bidirectional gated recurrent unit and attention mechanism with advanced optimization algorithms.

Scientific reports
Social-emotional learning (SEL) is gradually becoming a region of attention for defining children's school readiness and forecasting academic success. It is the procedure of incorporating cognition, behaviour, and emotion into daily life. School stru...

Intelligent feature fusion with dynamic graph convolutional recurrent network for robust object detection to assist individuals with disabilities in a smart Iot edge-cloud environment.

Scientific reports
Smart Internet of Things (IoT)-edge-cloud computing defines intelligent systems where IoT devices create data at the network's edge, which is then further processed and analyzed in local edge devices before transmission to the cloud for deeper insigh...

Hybrid intelligence in medical image segmentation.

Scientific reports
Medical image segmentation is vital for precise identification and analysis of anatomical structures and pathological regions, yet traditional models often fall short in aligning with clinical workflows, requiring extensive manual correction even whe...

Patent protection of biological genetic resources based on deep learning and artificial intelligence.

Scientific reports
With the rapid development of artificial intelligence (AI), deep learning has provided new ideas for the patent protection of biological genetic resources in the field of intellectual property. This paper aims to explore the application of deep learn...