AIMC Topic: Neural Networks, Computer

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EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Scientific reports
Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema, is critical for diagnosis and treatment monitoring.However, existing models, including Convolutional Neural Networks (CNNs) and Transformers, strugg...

Localisation and classification of multi-stage caries on CBCT images with a 3D convolutional neural network.

Clinical oral investigations
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...

A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.

Physics in medicine and biology
Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilate...

A method for predicting postpartum depression via an ensemble neural network model.

Frontiers in public health
INTRODUCTION: Postpartum depression (PPD) has numerous adverse impacts on the families of new mothers and society at large. Early identification and intervention are of great significance. Although there are many existing machine learning classifiers...

Deep learning models for segmenting phonocardiogram signals: a comparative study.

PloS one
Cardiac auscultation requires the mechanical vibrations occurring on the body's surface, which carries a range of sound frequencies. These sounds are generated by the movement and pulsation of different cardiac structures as they facilitate blood cir...

Driving scene image Dehazing model based on multi-branch and multi-scale feature fusion.

Neural networks : the official journal of the International Neural Network Society
Image dehazing is critical for enhancing image quality in applications such as autonomous driving, surveillance, and remote sensing. This paper presents an innovative image dehazing model based on a multi-branch and multi-scale feature fusion network...

Explainable AI for lung cancer detection via a custom CNN on CT images.

Scientific reports
Lung cancer, which claims 1.8 million lives annually, is still one of the leading causes of cancer-related deaths globally. Patients with lung cancer frequently have a bad prognosis because of late-stage detection, which severely limits treatment opt...

The satisfaction of ecological environment in sports public services by artificial intelligence and big data.

Scientific reports
In order to gain a more accurate understanding and enhance the relationship between the fitness ecological environment and artificial intelligence (AI)-driven sports public services, this study combines a Convolutional Neural Network (CNN) approach b...

Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images.

Scientific reports
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...

Design of a fractional-order environmental toxin-plankton system in aquatic ecosystems: A novel machine predictive expedition with nonlinear autoregressive neuroarchitectures.

Water research
Artificial intelligence has transformed both plankton dynamics and hazardous material management under toxic environments by enhanced hazard prediction in detecting how toxins affect plankton population and potentially uncovering greater depth of eco...