AIMC Topic: Convolutional Neural Networks

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Feature-based detection of breast cancer using convolutional neural network and feature engineering.

Scientific reports Sep 27, 2024
Breast cancer (BC) is a prominent cause of female mortality on a global scale. Recently, there has been growing interest in utilizing blood and tissue-based biomarkers to detect and diagnose BC, as this method offers a non-invasive approach. To impro...
Female Machine Learning Humans Breast Neoplasms Data Analysis Convolutional Neural Networks Biomarkers Datasets as Topic Computer Simulation Data Display
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Skin Cancer Detection in Diverse Skin Tones by Machine Learning Combining Audio and Visual Convolutional Neural Networks.

Oncology Sep 23, 2024
INTRODUCTION: Skin cancer (SC) is common in fair skin (FS) at a 1:5 lifetime incidence for nonmelanoma skin cancer. In order to assist clinicians' decisions, a risk intervention technology was developed, which combines a dual-mode machine learning of...
Convolutional Neural Networks ROC Curve Smartphone Skin Pigmentation Adult Sensitivity and Specificity Male Middle Aged Retrospective Studies Female Skin Neoplasms Aged Neural Networks, Computer Machine Learning Algorithms Humans
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High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Sep 22, 2024
PURPOSE: Evaluation of long-leg standing radiographs (LSR) is a standardised procedure for analysis of primary or secondary deformities of the lower limbs. Deep-learning convolutional neural networks (CNN) offer the potential to enhance radiological ...
Neural Networks, Computer Retrospective Studies Female Reproducibility of Results Humans Lower Extremity Radiography Knee Joint Arthroplasty, Replacement, Knee Osteoarthritis, Knee Aged Male Middle Aged Convolutional Neural Networks
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Radiation dose reduction in pediatric computed tomography (CT) using deep convolutional neural network denoising.

Clinical radiology Sep 21, 2024
AIM: We evaluated the quality of noncontrast chest computed tomography (CT) for pediatric patients at two dose levels with and without denoising using a deep convolutional neural network (CNN).
Retrospective Studies Tomography, X-Ray Computed Female Male Adolescent Child, Preschool Child Infant Convolutional Neural Networks Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Radiography, Thoracic
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Multimodal convolutional neural network-based algorithm for real-time detection and differentiation of malignant and inflammatory biliary strictures in cholangioscopy: a proof-of-concept study (with video).

Gastrointestinal endoscopy Sep 13, 2024
BACKGROUND AND AIMS: Deep learning algorithms gained attention for detection (computer-aided detection [CADe]) of biliary tract cancer in digital single-operator cholangioscopy (dSOC). We developed a multimodal convolutional neural network (CNN) for ...
Aged Sensitivity and Specificity Male Middle Aged Diagnosis, Computer-Assisted Humans Neural Networks, Computer Algorithms Female Cholangiocarcinoma Endoscopy, Digestive System Biliary Tract Neoplasms Cholestasis Constriction, Pathologic Cholangitis Deep Learning Video Recording Bile Duct Neoplasms Convolutional Neural Networks Proof of Concept Study ROC Curve Diagnosis, Differential
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Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).

Journal of imaging informatics in medicine Sep 12, 2024
The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delineations generated using a convolutional neural network (CNN). One hundred eighty-six CT scans from 48 PM patients were segmented...
Mesothelioma Pleural Neoplasms Probability Tumor Burden Male Middle Aged Convolutional Neural Networks Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Female Aged Humans Neural Networks, Computer
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Skeleton-guided 3D convolutional neural network for tubular structure segmentation.

International journal of computer assisted radiology and surgery Sep 12, 2024
PURPOSE: Accurate segmentation of tubular structures is crucial for clinical diagnosis and treatment but is challenging due to their complex branching structures and volume imbalance. The purpose of this study is to propose a 3D deep learning network...
Convolutional Neural Networks Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted Neural Networks, Computer Humans Tomography, X-Ray Computed Deep Learning
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A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases.

Journal of imaging informatics in medicine Aug 26, 2024
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There is increasing availability of non-enhanced CT (NE-CT) of the brain, mainly owing to a wider utilization of Positron Emission Tomography-CT (PET-CT) in...
Aged Aged, 80 and over Adult Brain Neoplasms Magnetic Resonance Imaging Male Humans Brain Middle Aged Retrospective Studies Neural Networks, Computer Convolutional Neural Networks Tomography, X-Ray Computed Imaging, Three-Dimensional Female
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Deep Convolutional Neural Network for Automated Staging of Periodontal Bone Loss Severity on Bite-wing Radiographs: An Eigen-CAM Explainability Mapping Approach.

Journal of imaging informatics in medicine Aug 15, 2024
Periodontal disease is a significant global oral health problem. Radiographic staging is critical in determining periodontitis severity and treatment requirements. This study aims to automatically stage periodontal bone loss using a deep learning app...
Convolutional Neural Networks Alveolar Bone Loss Male Middle Aged Severity of Illness Index Deep Learning Humans Neural Networks, Computer Female Adult
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Functional Near-Infrared Spectroscopy-Based Computer-Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter-Hemispheric Asymmetry in Prefrontal Hemodynamic Responses.

Depression and anxiety Jul 14, 2024
BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is being extensively explored as a potential primary screening tool for major depressive disorder (MDD) because of its portability, cost-effectiveness, and low susceptibility to motion artifac...
Spectroscopy, Near-Infrared Adult Humans Convolutional Neural Networks Deep Learning Male Prefrontal Cortex Neural Networks, Computer Functional Neuroimaging Hemodynamics Middle Aged Female Diagnosis, Computer-Assisted Depressive Disorder, Major Young Adult
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