AIMC Topic: Convolutional Neural Networks

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Use of a Convolutional Neural Network to Predict the Response of Diabetic Macular Edema to Intravitreal Anti-VEGF Treatment: A Pilot Study.

American journal of ophthalmology Feb 20, 2025
PURPOSE: To utilize a convolutional neural network (CNN) to predict the response of treatment-naïve diabetic macular edema (DME) to a single injection of anti-vascular endothelial growth factor (anti-VEGF) with data from optical coherence tomography ...
Treatment Outcome Humans Follow-Up Studies Diabetic Retinopathy Visual Acuity Neural Networks, Computer Tomography, Optical Coherence Retrospective Studies Macular Edema Vascular Endothelial Growth Factor A Intravitreal Injections Ranibizumab Bevacizumab Female Aged Male Middle Aged Convolutional Neural Networks Pilot Projects Angiogenesis Inhibitors
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A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.

Ecotoxicology and environmental safety Feb 19, 2025
Soil pollution caused by toxic metals poses serious threats to the ecological environment and human well-being. Accurately predicting toxic metal concentrations is critical for safeguarding soil environmental security. However, the distribution of so...
Environmental Pollution Convolutional Neural Networks Cadmium Environmental Monitoring Neural Networks, Computer Soil Pollutants Soil Arsenic
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Convolutional neural network for gesture recognition human-computer interaction system design.

PloS one Feb 19, 2025
Gesture interaction applications have garnered significant attention from researchers in the field of human-computer interaction due to their inherent convenience and intuitiveness. Addressing the challenge posed by the insufficient feature extractio...
Convolutional Neural Networks Humans Gestures Neural Networks, Computer Algorithms User-Computer Interface Pattern Recognition, Automated
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Interpretation of basal nuclei in brain dopamine transporter scans using a deep convolutional neural network.

Nuclear medicine communications Feb 18, 2025
OBJECTIVE: Functional imaging using the dopamine transporter (DAT) as a biomarker has proven effective in assessing dopaminergic neuron degeneration in the striatum. In assessing the neuron degeneration, visual and semiquantitative methods are used t...
Neural Networks, Computer Brain Retrospective Studies Female Humans Convolutional Neural Networks Image Processing, Computer-Assisted Parkinson Disease Image Interpretation, Computer-Assisted Aged Male Middle Aged Deep Learning Tomography, Emission-Computed, Single-Photon Dopamine Plasma Membrane Transport Proteins
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Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Cancer imaging : the official publication of the International Cancer Imaging Society Feb 18, 2025
BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...
Humans Neural Networks, Computer Fluorodeoxyglucose F18 Lung Neoplasms Solitary Pulmonary Nodule Male Retrospective Studies Positron Emission Tomography Computed Tomography Middle Aged Female Radiopharmaceuticals Convolutional Neural Networks Aged Adult
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Sway frequencies may predict postural instability in Parkinson's disease: a novel convolutional neural network approach.

Journal of neuroengineering and rehabilitation Feb 18, 2025
BACKGROUND: Postural instability greatly reduces quality of life in people with Parkinson's disease (PD). Early and objective detection of postural impairments is crucial to facilitate interventions. Our aim was to use a convolutional neural network ...
Parkinson Disease Postural Balance Humans Neural Networks, Computer Female Aged Male Middle Aged Convolutional Neural Networks
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Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.

Journal of orthopaedic surgery and research Feb 14, 2025
BACKGROUND: Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We h...
Convolutional Neural Networks Adolescent Child Neural Networks, Computer Mass Screening Female Male Scoliosis Deep Learning Humans Back
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.

PloS one Feb 13, 2025
This study aims to solve the problems of insufficient accuracy and low efficiency of the existing methods in sprint pattern recognition to optimize the training and competition strategies of athletes. Firstly, the data collected in this study come fr...
Athletes Convolutional Neural Networks Humans Support Vector Machine Machine Learning Random Forest Computer Simulation Running Biomechanical Phenomena Pattern Recognition, Automated Track and Field
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Classification of fundus autofluorescence images based on macular function in retinitis pigmentosa using convolutional neural networks.

Japanese journal of ophthalmology Feb 12, 2025
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
Adult Male Middle Aged Convolutional Neural Networks Retrospective Studies Visual Fields Humans Adolescent Female Fluorescein Angiography Neural Networks, Computer Visual Acuity Aged Macula Lutea Tomography, Optical Coherence Young Adult Retinitis Pigmentosa Fundus Oculi
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Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

International journal of molecular sciences Feb 11, 2025
The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding disease mechanisms and identifying potential therapeutic targets. Traditional methods often struggle to cope with the complexity of heterogeneous network...
Humans Neural Networks, Computer Algorithms Convolutional Neural Networks Computational Biology Pharmaceutical Preparations Autoencoder RNA, Circular
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