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Deep convolutional neural network VGG-16 model for differential diagnosing of papillary thyroid carcinomas in cytological images: a pilot study

https://doi.org/10.7150/jca.28769
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cncy.21915openalex-snapshot
Computer‐assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis
inferredcites →https://doi.org/10.1002/dc.2840070410openalex-snapshot
Fxine‐needle aspiration biopsy of papillary thyroid carcinoma: Cytologic, histologic, and ultrastructural correlations
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Thyroid cancer mortality and incidence: A global overview
inferredcites →https://doi.org/10.1007/s13246-013-0199-8openalex-snapshot
Computer-aided diagnosis system for classifying benign and malignant thyroid nodules in multi-stained FNAB cytological images
inferredcites →https://doi.org/10.1016/j.cmpb.2011.12.007openalex-snapshot
Histology image analysis for carcinoma detection and grading
inferredcites →https://doi.org/10.1016/j.compbiomed.2016.11.003openalex-snapshot
Classification of teeth in cone-beam CT using deep convolutional neural network
inferredcites →https://doi.org/10.1016/j.media.2015.12.002openalex-snapshot
Automated classification of brain tumor type in whole-slide digital pathology images using local representative tiles
inferredcites →https://doi.org/10.1089/thy.2009.0274openalex-snapshot
The Bethesda System for Reporting Thyroid Cytopathology
inferredcites →https://doi.org/10.1089/thy.2015.0020openalex-snapshot
2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: The American Thyroid Association Guidelines Task Force on Thyroid Nodules and Differentiated Thyroid Cancer
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/tmi.2016.2535865openalex-snapshot
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
inferredcites →https://doi.org/10.1118/1.4944498openalex-snapshot
Urinary bladder segmentation in CT urography using deep‐learning convolutional neural network and level sets
inferredcites →https://doi.org/10.1118/1.4948498openalex-snapshot
Automated detection of pulmonary nodules in PET/CT images: Ensemble false‐positive reduction using a convolutional neural network technique
inferredcites →https://doi.org/10.1155/2017/4067832openalex-snapshot
Automated Classification of Lung Cancer Types from Cytological Images Using Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1159/000339959openalex-snapshot
The Bethesda System for Reporting Thyroid Cytopathology: A Meta-Analysis
inferredcites →https://doi.org/10.1309/ajcpphlwmi3jv4laopenalex-snapshot
The Bethesda System for Reporting Thyroid Cytopathology
inferredcites →https://doi.org/10.3322/caac.20138openalex-snapshot
Cancer statistics, 2012
inferredcites →https://doi.org/10.4103/1742-6413.48606openalex-snapshot
The impact of digital imaging in the field of cytopathology
inferredcites →https://doi.org/10.4103/jpi.jpi_34_17openalex-snapshot
Deep Learning for Classification of Colorectal Polyps on Whole-slide Images
inferredcites →https://doi.org/10.48550/arxiv.1409.1556openalex-snapshot
Very Deep Convolutional Networks for Large-Scale Image Recognition
inferredcites →https://doi.org/10.7314/apjcp.2013.14.1.97openalex-snapshot
Support Vector Machine Based Diagnostic System for Thyroid Cancer using Statistical Texture Features
inferredcites →https://doi.org/10.7785/tcrt.2012.500430openalex-snapshot
Development of an Automated Medical Diagnosis System for Classifying Thyroid Tumor Cells using Multiple Classifier Fusion

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A comprehensive study for solar panel fault detection using VGG16 and VGG19 convolutional neural networks
inferred← citeshttps://doi.org/10.1109/iccnea60107.2023.00011openalex-snapshot
MA-Unet3+ Segmentation Network of Remote Sensing Image Based on ECA Block
inferred← citeshttps://doi.org/10.1109/iceca52323.2021.9676146openalex-snapshot
Detecting Pneumonia using Vision Transformer and comparing with other techniques
inferred← citeshttps://doi.org/10.1109/icecct52121.2021.9616623openalex-snapshot
Deep Learning Approaches for Detection of Covid-19 Using Chest X-Ray Images
inferred← citeshttps://doi.org/10.1109/icesic53714.2022.9783566openalex-snapshot
Blur Classification and Estimation of Motion Blur Parameters Using OLR
inferred← citeshttps://doi.org/10.1109/icetet-sip-2254415.2022.9791585openalex-snapshot
Enhancement in Dentistry using Machine Learning: A Systematic Review
inferred← citeshttps://doi.org/10.1109/icetetsip64213.2025.11156903openalex-snapshot
Automated Dental Image Segmentation Using U-Net with VGG-16 Backbone
inferred← citeshttps://doi.org/10.1109/icfpt59805.2023.00023openalex-snapshot
SSiMD: Supporting Six Signed Multiplications in a DSP Block for Low-Precision CNN on FPGAs
inferred← citeshttps://doi.org/10.1109/icici62254.2024.00024openalex-snapshot
Skin Cancer Diagnosis using Deep Learning, Transfer Learning and Hybrid Model
inferred← citeshttps://doi.org/10.1109/icicis58388.2023.10391135openalex-snapshot
Mobile Application for Heart Diseases Diagnosis based on the PPG Signals and Deep Learning
inferred← citeshttps://doi.org/10.1109/icicsp62589.2024.10809123openalex-snapshot
Ship-Radiated Noise Recognition Based on Swin-Transformer
inferred← citeshttps://doi.org/10.1109/icisat54145.2021.9678481openalex-snapshot
Gastrointestinal image classification based on VGG16 and transfer learning
inferred← citeshttps://doi.org/10.1109/icmcsi64620.2025.10883627openalex-snapshot
Obstacle Avoidance: Transfer Learning and FPGA for Acceleration
inferred← citeshttps://doi.org/10.1109/icmee59781.2023.10525574openalex-snapshot
Comparative Analysis of Transfer Learning and Customized Deep Convolutional Neural Networks for Breast Cancer Detection and Classification
inferred← citeshttps://doi.org/10.1109/icmi65310.2025.11141174openalex-snapshot
A Performance Comparison of VGG16 for Cancer Cell Classification
inferred← citeshttps://doi.org/10.1109/icnsc55942.2022.10004063openalex-snapshot
Detection of Face Mask Wearing for COVID-19 Protection based on Transfer Learning and Classic CNN Model
inferred← citeshttps://doi.org/10.1109/icsft67370.2026.11566177openalex-snapshot
Deep Learning Architectures for Ophthalmic Diagnosis: Evaluating CNN, VGG16, ResNet50, and Inception V3 in Myopia Detection
inferred← citeshttps://doi.org/10.1109/idciot56793.2023.10053392openalex-snapshot
Identification of Malignant Patterns in FNAC Digital Images of Thyroid Nodules through Cascaded Segmentation Stages
inferred← citeshttps://doi.org/10.1109/ieca66054.2025.00011openalex-snapshot
Multi-head graph attention network for human pose recognition
inferred← citeshttps://doi.org/10.1109/imcom64595.2025.10857556openalex-snapshot
Measuring the Performance of VGG-16, VGG-19, and a Concatenated Model Architecture in Toraja Carving Classification
inferred← citeshttps://doi.org/10.1109/incet61516.2024.10593144openalex-snapshot
MRI Scans for Deep Learning-Based Chronic Nephropathy Detection: A Comparison of CNN, MobileNet, VGG16, and ResNet-50 Models
inferred← citeshttps://doi.org/10.1109/ised59382.2023.10444592openalex-snapshot
Lung Disease Classification using X-Ray Imaging with Ensemble Learning
inferred← citeshttps://doi.org/10.1109/jac-ecc54461.2021.9691433openalex-snapshot
A robust CNN classification of whole slide thyroid carcinoma images
inferred← citeshttps://doi.org/10.1109/lawp.2022.3174357openalex-snapshot
Regression of Large-Scale Path Loss Parameters Using Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/prai59366.2023.10331956openalex-snapshot
Design a Method for Tracking Moving Object and Predicting its Trajectory in a Noisy Environment
inferred← citeshttps://doi.org/10.1109/sipaim56729.2023.10373523openalex-snapshot
UltraCytomic: A cross-scale exploration to improve risk estimation of the malignant thyroid nodule
inferred← citeshttps://doi.org/10.1109/tbcas.2020.3036081openalex-snapshot
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
inferred← citeshttps://doi.org/10.1109/tim.2021.3052018openalex-snapshot
Online monitoring of green pellet size distribution in haze-degraded images based on VGG16-LU-net and haze judgement
inferred← citeshttps://doi.org/10.1109/tmc.2025.3647481openalex-snapshot
Condensed Semantic Communication for 360$^{\circ }$∘ Image Transmission
inferred← citeshttps://doi.org/10.1109/trpms.2022.3231702openalex-snapshot
Pre-Training, Transfer Learning and Pretext Learning for a Convolutional Neural Network Applied to Automated Assessment of Clinical PET Image Quality
inferred← citeshttps://doi.org/10.1109/trpms.2024.3436697openalex-snapshot
Deep Convolutional Backbone Comparison for Automated PET Image Quality Assessment
inferred← citeshttps://doi.org/10.1109/ubmk67458.2025.11206866openalex-snapshot
A Multimodal AI and ML Framework for Fashion Image Segmentation, Recommendation, and Similarity Recognition
inferred← citeshttps://doi.org/10.1109/wf-iot62078.2024.10811358openalex-snapshot
UAV-Based Efficient and Reliable Wildfire Detection on the Edge
inferred← citeshttps://doi.org/10.11106/ijt.2025.18.1.6openalex-snapshot
The Evolution of Digital Pathology in Infrastructure, Artificial Intelligence and Clinical Impact
inferred← citeshttps://doi.org/10.1111/cas.15930openalex-snapshot
Deep learning prediction model for central lymph node metastasis in papillary thyroid microcarcinoma based on cytology
inferred← citeshttps://doi.org/10.1111/cyt.12942openalex-snapshot
The emerging role of deep learning in cytology
inferred← citeshttps://doi.org/10.1111/cyt.70045openalex-snapshot
Application of Artificial Intelligence–Based Transfer Learning Models to the Bethesda System for Thyroid Cytopathology
inferred← citeshttps://doi.org/10.1117/1.jmi.9.6.067501openalex-snapshot
Cell2Grid: an efficient, spatial, and convolutional neural network-ready representation of cell segmentation data
inferred← citeshttps://doi.org/10.1142/s0218001423560244openalex-snapshot
A Convolutional Neural Network Based on Soft Attention Mechanism and Multi-Scale Fusion for Skin Cancer Classification
inferred← citeshttps://doi.org/10.1142/s0219467825500275openalex-snapshot
Development of Trio Optimal Feature Extraction Model for Attention-Based Adaptive Weighted RNN-Based Lung and Colon Cancer Detection Framework Using Histopathological Images
inferred← citeshttps://doi.org/10.1142/s1793962325410235openalex-snapshot
Modeling a novel vision transformer with attention mechanism and pre-trained network model for medical image analysis
inferred← citeshttps://doi.org/10.1145/3436369.3436452openalex-snapshot
Latent Melanoma Skin Cancer Image Classification by using Depthwise Separable CNN
inferred← citeshttps://doi.org/10.1145/3466690openalex-snapshot
AIDCOV: An Interpretable Artificial Intelligence Model for Detection of COVID-19 from Chest Radiography Images
inferred← citeshttps://doi.org/10.1145/3573942.3574109openalex-snapshot
Steel Defect Detection Based on Yolov5
inferred← citeshttps://doi.org/10.1155/2021/5755671openalex-snapshot
Effect of Interventional Therapy on Iliac Venous Compression Syndrome Evaluated and Diagnosed by Artificial Intelligence Algorithm-Based Ultrasound Images
inferred← citeshttps://doi.org/10.1155/2021/9612480openalex-snapshot
Truck-Lifting Prevention System Based on Vision Tracking for Container-Lifting Operation
inferred← citeshttps://doi.org/10.1155/2022/1828782openalex-snapshot
[Retracted] Correlation Analysis between the Emotion and Aesthetics for Chinese Classical Garden Design Based on Deep Transfer Learning
inferred← citeshttps://doi.org/10.1155/2022/3070361openalex-snapshot
Deep Learning-Based MR Imaging for Analysis of Relation between Cerebrospinal Fluid Variation and Communicating Hydrocephalus after Decompressive Craniectomy for Craniocerebral Injury
inferred← citeshttps://doi.org/10.1155/2024/3790617openalex-snapshot
Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning
inferred← citeshttps://doi.org/10.1159/000512097openalex-snapshot
Artificial Intelligence in Thyroid Fine Needle Aspiration Biopsies
inferred← citeshttps://doi.org/10.1177/00034894231158464openalex-snapshot
Lymph Node Metastases in Papillary Thyroid Carcinoma can be Predicted by a Convolutional Neural Network: a Multi-Institution Study
inferred← citeshttps://doi.org/10.1177/00220345211009474openalex-snapshot
Automated Radiographic Evaluation of Adenoid Hypertrophy Based on VGG-Lite
inferred← citeshttps://doi.org/10.1186/s12859-023-05543-2openalex-snapshot
EMDL_m6Am: identifying N6,2′-O-dimethyladenosine sites based on stacking ensemble deep learning
inferred← citeshttps://doi.org/10.1186/s12911-024-02658-1openalex-snapshot
Analysis of anterior segment in primary angle closure suspect with deep learning models
inferred← citeshttps://doi.org/10.1186/s13000-025-01618-1openalex-snapshot
Annotation-free genetic mutation estimation of thyroid cancer using cytological slides from multi-centers
inferred← citeshttps://doi.org/10.1186/s43042-024-00522-5openalex-snapshot
Artificial intelligence-driven enhanced skin cancer diagnosis: leveraging convolutional neural networks with discrete wavelet transformation
inferred← citeshttps://doi.org/10.12659/msm.939462openalex-snapshot
Improving Renal Tumor Diagnosis with Computed Tomography and Artificial Neural Networks
inferred← citeshttps://doi.org/10.12928/telkomnika.v22i2.25840openalex-snapshot
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
inferred← citeshttps://doi.org/10.1364/ao.486107openalex-snapshot
LaserNet: a method of laser stripe center extraction under non-ideal conditions
inferred← citeshttps://doi.org/10.1364/oe.443932openalex-snapshot
Machine learning for sensing with a multimode exposed core fiber specklegram sensor
inferred← citeshttps://doi.org/10.1371/journal.pone.0312998openalex-snapshot
Hierarchical-Concatenate Fusion TDNN for sound event classification
inferred← citeshttps://doi.org/10.14341/probl13475openalex-snapshot
Prospects for the application of convolutional neural networks in the cytological diagnosis of thyroid nodules
inferred← citeshttps://doi.org/10.14500/aro.12024openalex-snapshot
A Novel Skin Cancer Detection Approach Using Deep Learning Algorithm with Image Segmentation Filters
inferred← citeshttps://doi.org/10.1515/dema-2023-0262openalex-snapshot
Toward automated hail disaster weather recognition based on spatio-temporal sequence of radar images
inferred← citeshttps://doi.org/10.15575/join.v8i1.1051openalex-snapshot
Malware Image Classification Using Deep Learning InceptionResNet-V2 and VGG-16 Method
inferred← citeshttps://doi.org/10.17116/patol20268802167openalex-snapshot
Potential applications of artificial intelligence technology in assessing mitotic activity of gastrointestinal stromal tumors of the stomach
inferred← citeshttps://doi.org/10.17586/2226-1494-2024-24-1-51-61openalex-snapshot
An improved performance of RetinaNet model for hand-gun detection in custom dataset and real time surveillance video
inferred← citeshttps://doi.org/10.18495/comengapp.v11i3.406openalex-snapshot
Detection of Diabetic Retinopathy Using Convolutional Neural Network (CNN)
inferred← citeshttps://doi.org/10.21037/atm-21-4328openalex-snapshot
Thyroid ultrasound image classification using a convolutional neural network
inferred← citeshttps://doi.org/10.21037/gs-23-486openalex-snapshot
Deep convolutional neural network model ResNeSt for discrimination of papillary thyroid carcinomas and benign nodules in thyroid nodules diagnosed as atypia of undetermined significance
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