Deep convolutional neural network based medical image classification for disease diagnosis

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Predicting Orthopedic Surgery Types Using Convolutional Neural Networks

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DepthParkNet: A 3D Convolutional Neural Network with Depth-Aware Coordinate Attention for PET-Based Parkinson's Disease Diagnosis

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Brain Storm Optimization based Swarm Learning for Diabetic Retinopathy Image Classification

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Automated fingerprint analysis as a diagnostic tool for the genetic disorder Kabuki syndrome

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Using the Fuzzy Integrals for the Ensemble-Based Classification Problem PCB Defects

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Artificial Intelligence in Cancer: A SWOT Analysis

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Zero-Shot Image Classification: Recent Status and Future Trends

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Feature Extraction of Human Palm Prints Based on Machine Vision

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Feature Techniques with a Custom Convolutional Model for Breast Tumor Surveillance in Mammograms

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Maintaining Sanity: Algorithm-based Comprehensive Fault Tolerance for CNNs

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Knee Osteoarthritis Image Classification Based on A Novel Multi-granularity Feature Fusion Network

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Detection of OSA Through the Application of Deep Learning on Polysomnography Data

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Training Neural Networks with a Procedure Guided by BNF Grammars

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Design an Artificial Intelligence Based Machine Learning Framework for Improving Health Care Management

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Preemptive Diagnosis of Parkinson’s Disease Through DaT Scans Using InceptionV3-Based Convolutional Neural Network

Appineni, A., & Gupta, A. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-97-9045-6_3 · Cited by 1

Method for detecting non-alcoholic fatty liver disease in abdominal thermography time series using temporal convolutional networks

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Automated Pneumonia Diagnosis from Chest X-Rays Using Deep Learning Models

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Development of an artificial intelligence-based convolutional neural network for sellar barrier classification using magnetic resonance imaging

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ISLO-Tuned InceptionResNetV2 and 3D U-Net: A Powerful Duo for Automated Renal Cancer Diagnosis

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Optimizing MCMC-Driven Bayesian Neural Networks for High-Precision Medical Image Classification in Small Sample Sizes

Sun, M. (2025) · International Conference on Algorithm, Artificial Intelligence and Computer Vision (AAICV) · doi:10.1109/aaicv66571.2025.00060 · Cited by 1

Enhancing visual and semantic alignment of multimodal large models in medical images

Liu, Q., Fang, Y., & Liu, X. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07859-7 · Cited by 1

An Ensemble of Deep Semantic Representation for Medical X-ray Image Classification

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Performance Measures of Respiratory Disease Classification using Deep Learning

Janani, G. R. (2021) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2021.35109 · Cited by 1

HFMD Skin Rash Detection Using Convolutional Neural Networks

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Chest X-Ray Image Analysis of Convolutional Neural Network Models with Transfer Learning for Prediction of COVID Patients

Devi, M. S., Swathi, P. G., Kumar, N. P., Tungala, R. V., Vivekanandan, S., & Moorthy, P. (2021) · Smart innovation, systems and technologies · doi:10.1007/978-981-16-1502-3_36 · Cited by 1

Application of Fuzzy Convolutional Neural Network for Disease Diagnosis: A Case of Covid-19 Diagnosis Through CT Scanned Lung Images

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Use of Deep Learning Based Frameworks on Pixel Scaled Images of Chest CT Scans for Detection of COVID-19

Shetty, S., Gawade, A., & Deolekar, S. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-74761-9_4 · Cited by 1

Weakly Supervised Breast Lesions Detection in Dynamic Contrast Enhancement Magnetic Resonance Imaging

Wei, C., & Nie, S. (2021) · International Conference on Systems and Informatics (ICSAI) · doi:10.1109/icsai53574.2021.9664072 · Cited by 1

On the Feasibility of Privacy-Secured Facial Authentication for low-power IoT Devices - Quantifying the Effects of Head Pose Variation on End-to-End Neural Face Recognition

Yao, W., Varkarakis, V., Lemley, J., & Corcoran, P. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/fevr2516 · Cited by 1

A machine vision system for avian song classification with CNN’s

Palma, G., Aquino, A., Monticelli, P., Verdade, L. M., Markham, C., & Moral, R. D. A. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/mhzn4111 · Cited by 1

Machine Learning

Uddin, M. Z. (2022) · Springer eBooks · doi:10.1007/978-3-031-11534-9_3 · Cited by 2

Multiple Feature based Classification for the Prediction of Brain Tumor

Chhabra, P., & Bhatia, P. K. (2022) · International Conference on Parallel, Distributed and Grid Computing (PDGC) · doi:10.1109/pdgc56933.2022.10053350 · Cited by 1

Classification of Chest X-ray Images using CNN for Medical Decision Support System

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Causal Analysis of Bone Disease Risk Factors Based on Markov Boundary Discovery

Liu, L., Wang, H., Zhu, Y., Ge, N., & Hu, S. (2023) · International Conference on Big Data and Information Analytics (BigDIA) · doi:10.1109/bigdia60676.2023.10429564 · Cited by 1

Fabric Image Representation Encoding Networks for Large-scale 3D Medical Image Analysis.Preprint

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Measles Rash Identification Using Residual Deep Convolutional Neural NetworkPreprint

Glock, K., Napier, C., Louie, A., Gary, T., Gigante, J., Schaffner, W., & Wang, Q. (2020) · arXiv (Cornell University) · Cited by 1

A comparison of deep machine learning algorithms in COVID-19 disease diagnosisPreprint

Yadav, S. S., Sandhu, J. K., Bendre, M. R., Vikhe, P. S., & Kaur, A. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2008.11639 · Cited by 1

Image Classification using ImageNet Classifiers in Environments with Limited DataPreprint

Sharma, A., Singh, A. K., Choudhury, T., & Sarkar, T. (2021) · Research Square · doi:10.21203/rs.3.rs-428416/v1 · Cited by 1

TeliNet, a simple and shallow Convolution Neural Network (CNN) to Classify CT Scans of COVID-19 patients.Preprint

Teli, M. N. (2021) · arXiv (Cornell University) · Cited by 1

Hand Foot and Mouth Rash Detection Using Deep Convolution Neural NetworkPreprint

Vakili, N., Chan, J. H., Krathu, W., Phattarakijtham, N., & Hirata, K. (2021) · doi:10.36227/techrxiv.13725448 · Cited by 1

CircWaveNet: A New Conventional Neural Network Based on Combination of Circlets and Wavelets for Macular OCT ClassificationPreprint

Arian, R., Vard, A., Kafieh, R., Plonka, G., & Rabbani, H. (2023) · medRxiv · doi:10.1101/2023.09.23.23295997 · Cited by 1

Adapt the Parameters of RBF Networks Using Grammatical EvolutionPreprint

Tsoulos, I. G., Tzallas, A. T., & Karvounis, E. C. (2023) · Preprints.org · doi:10.20944/preprints202309.1532.v1 · Cited by 1

Preemptive Diagnosis of Parkinson's Disease through DaT Scans using InceptionV3-based Convolutional Neural NetworksPreprint

Appineni, A., & Gupta, A. (2023) · Preprints.org · doi:10.20944/preprints202312.2268.v1 · Cited by 1

Big Data Analysis in Personalized Medicine

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Human Pose Estimation Based on the Multistage Learning and the Dense Connection

Shi, W., Yang, Q., & Chen, J. (2020) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei51763.2020.9263617

Peer Review #2 of "Stem cell imaging through convolutional neural networks: current issues and future directions in artificial intelligence technology (v0.1)"

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B-mode Ultrasound Texture Recognition Algorithm of Liver Based on Random Forests

Li, H., Yang, L., He, T., Xiao, Y., Liang, Z., & Wu, X. (2020) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei51763.2020.9263593

Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy

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Well-Known brands recognition by automated classifiers using local and global features

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Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopyPreprint

Brochet, T., Lapuyade‐Lahorgue, J., Bougleux, S., Salaün, M., & Ruan, S. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.05450

Smart Approach for Identification of Pneumonia Using Real-Time Convolutional Neural Networks

Dalwadi, D. C., Mehta, Y., Patel, N., Macwan, N., & Sakhiya, D. (2021) · Communications in computer and information science · doi:10.1007/978-981-16-3660-8_20

Multi-Scale Context Interaction Learning network for Medical Image Segmentation

Fang, W., Han, X., Xu, Q., Jiang, H., & Chen, Y. (2021) · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR) · doi:10.1109/mipr51284.2021.00036 · Cited by 1

Peer Review #1 of "Stem cell imaging through convolutional neural networks: current issues and future directions in artificial intelligence technology (v0.2)"

(2020) · PeerJ · doi:10.7287/peerj.10346v0.2/reviews/1

Bayesian Competing Risk Model for Medical Data

Devana, N., & Abdullah, S. (2021) · Advances in engineering research/Advances in Engineering Research · doi:10.2991/aer.k.211222.003

Prediction of Hospital Outpatient Volume Based on Combined Neural Network

Chen, Z., & Li, W. (2021) · International Conference on Systems and Informatics (ICSAI) · doi:10.1109/icsai53574.2021.9664145

Peer Review #1 of "Stem cell imaging through convolutional neural networks: current issues and future directions in artificial intelligence technology (v0.1)"

(2020) · PeerJ · doi:10.7287/peerj.10346v0.1/reviews/1

Machine Hearing a Cognitive Service for Aiding Clinical Diagnosis

Gopi, A., & Sajini, T. (2022) · Communications in computer and information science · doi:10.1007/978-3-030-95711-7_26

AIM in Interventional Radiology

Datta, S. (2022) · Springer eBooks · doi:10.1007/978-3-030-64573-1_283

Applications of Big Data in Fighting the COVID-19 and Future Employment

Li, K. (2021) · International Conference on Big Data Economy and Information Management (BDEIM) · doi:10.1109/bdeim55082.2021.00069

Contemporary Urban Space Philosophy in China Using Lightweight Deep Learning Model-Under Ecological Ethics

Cheng, H. (2022) · Computational Intelligence and Neuroscience · doi:10.1155/2022/8925205

Covid-19 Detection Using Chest Computed Tomography Scans on Ecuadorian Patients Who Live in the Highland Region

Jacho, K. J., Martinez, D. M., Guerrón, N., & Erazo-Rodas, M. (2021) · International Conference on Biomedical and Bioinformatics Engineering (ICBBE) · doi:10.1145/3502871.3502873

An embedded neuro-fuzzy architecture for explainable time series analysis

Xie, C. (2021) · doi:10.32657/10356/155536

Diagnosis of Brain Tumor Using Nano Segmentation and Advanced-cnn ClassificationPreprint

DEEPA, P. V., Joseph Jawhar, S., & Geisa, M. (2020) · doi:10.21203/rs.3.rs-80958/v1

Artificial Intelligence Aiding Medical Diagnosis Focusing on Diabetic Retinopathy

Juneja, S., Bali, A., & Bali, N. (2022) · Advances in medical diagnosis, treatment, and care (AMDTC) book series · doi:10.4018/978-1-6684-2304-2.ch003

Handwriting Slant Determination Using Convolutional Neural Networks and Transfer Learning

Meitei, C. M., Upadhyay, S., & Kumar, A. (2022) · IEEE International Conference for Convergence in Technology (I2CT) · doi:10.1109/i2ct54291.2022.9823963

Evaluation of Household Waste Image Identification Using Convolutional Neural NetworkPreprint

Sunardi, S., Yudhana, A., & Fahmi, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4168618

An NLP approach to Image Analysis

Martinez, G. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/kfbi5107

High-Fidelity Face Swapping with Style Blending

Yang, X., Guo, Z., Xue, M., & Shi, Z. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/kupa8487 · Cited by 1

Classification of electromagnetic interference induced image noise in an analog video link

Purcell, A. W., & Eising, C. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/zanb2627 · Cited by 1

Pre- and Post-Operative Analysis of Planar Radiographs in Total Hip Replacement

Denton, O., Madden-McKee, C., Hill, J., Beverland, D., Dunne, N., & Lennon, A. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/exjl3727

A Data Augmentation and Pre-processing Technique for Sign Language Fingerspelling Recognition

Fowley, F., Rushe, E., & Ventresque, A. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/xbav3102

Beyond Social Distancing: Application of real-world coordinates in a multi-camera system with privacy protection

Ryan, F., Hu, F., Dietlmeier, J., O'Connor, N. E., & McGuinness, K. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/rtns4233

Acoustic Source Localization Using Straight Line Approximations

Bagchi, S., & de Fréin, R. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/ljrb7078

Detection and Isolation of 3D Objects in Unstructured Environments

Couto, D. D., Butterfield, J., Murphy, A., Rafferty, K., & Coleman, J. (2022) · International Machine Vision and Image Processing Conference (IMVIP) · doi:10.56541/afmz9460

Deep learning for an improved diagnostic pathway of prostate cancer in a small multi-parametric magnetic resonance data regime

Fernández-Quilez, Á. (2022) · doi:10.31265/usps.197

Federated Machine Learning for Multi-Aspect Neuro-developmental Disorders

Shamseddine, H. (2022) · doi:10.26756/th.2022.508

Advancing photoacoustic tomography using deep learning

Rajendran, P. (2022) · doi:10.32657/10356/162207

SURVEY ON DIABETIC RETINOPATHY DETECTION

(2022) · International Research Journal of Modernization in Engineering Technology and Science · doi:10.56726/irjmets31540

3D point cloud target recognition based on the Bi-LSTM and PointCNN network

Cheng, P., Zhu, Q., & Wang, W. (2022) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp-bmei56279.2022.9980199

Application of GPU Accelerated Deep Learning Neural Networks for COVID-19 Recognition from X-Ray Scans

Nikolov, M., Tsenov, G. T., Nakov, O., Lazarova, M. K., & Mladenov, V. (2022) · International Scientific Conference on Computer Science (COMSCI) · doi:10.1109/comsci55378.2022.9912590

Robot swarm development as a learning tool

Bohórquez, F. S. P., Mora, A. S. L., Tello, S., Vera, Z., Baidal, E., Arroyo, O. O. A., & Plaza, A. (2022) · LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI) · doi:10.18687/laccei2022.1.1.621

Improved IoT for Health Behaviour System Based on Machine Learning Model

Shrivastava, A., Chakkaravarthy, M., & Shah, M. A. (2022) · International Conference on Technological Advancements in Computational Sciences (ICTACS) · doi:10.1109/ictacs56270.2022.9988468

Selected Deep Features and Multiclass SVM for Flower Image Classification

Banwaskar, M. R., Rajurkar, A. M., & Guru, D. S. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-22405-8_28

Covid Analysis Prediction Using Densenet Method in Deep Learning

Usha, M., Prittopaul, P., & Lekha, D. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-7169-3_24

Multi-feature Fusion Flame Detection Algorithm Based on BP Neural Network

Wu, J., Yang, L., Gao, Y., & Zhang, Z. (2023) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-031-20738-9_45

Overview of Recent Trends in Medical Image Processing

Chitra, P. (2023) · Advances in computer and electrical engineering book series · doi:10.4018/978-1-6684-6523-3.ch007

Deep CNN based Multi Classification of Respiratory Disease using X-Ray Images

Varalakshmi, S., Vijayalakshmi, P., & Rajendran, V. (2022) · International Conference on Power, Energy, Control and Transmission Systems (ICPECTS) · doi:10.1109/icpects56089.2022.10047331

An Ensemble MultiLabel Classifier for Intra-Cranial Haemorrhage Detection from Large, Heterogeneous and Imbalanced Database

Choudhary, B., Babu, A. R., & Talukdar, U. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-27609-5_26

A Survey on Diagnosing Pulmonary Diseases

Rao, A. S., Shamitha, S., Tarun, S. R. G., Priya, S. U., & Prasad, V. R. B. (2023) · IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS) · doi:10.1109/sceecs57921.2023.10063115

A modified CNN model for Brain Tumor Detection

Das, J. B. A., Das, A., Sarangi, A., Mishra, D., & Mohanty, M. N. (2022) · International Conference on Machine Learning, Computer Systems and Security (MLCSS) · doi:10.1109/mlcss57186.2022.00038

A Deep Ensemble Model for Differential Diagnosis of Covid-19 Pneumonia using Thoracic Radiography

Shekar, B. H., & Mannan, S. (2023) · International Conference on Signal Processing and Integrated Networks (SPIN) · doi:10.1109/spin57001.2023.10116517

Deep learning method for brain tumor identification with multimodal 3D-MRI

Yakaiah, P., Srikar, D., Kaushik, G., & Geetha, Y. (2023) · AIP conference proceedings · doi:10.1063/5.0116910

Prediction of Dementia Using Whale Optimization Algorithm Based Convolutional Neural Network

Moorthy, R. S., Arul, R., Kannan, K., & Kothandaraman, R. (2023) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-0047-3_25

Deep Learning in Medical Imaging

Benameur, N., & Mahmoudi, R. (2023) · Artificial intelligence · doi:10.5772/intechopen.111686 · Cited by 3

Artificial Intelligence for Enhancement of Brain Image Using Semantic Segmentation CNN with IoT Classification Techniques

Rupapara, V. (2023) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-031-23602-0_26

Medical X-ray Image Classification Method Based on Convolutional Neural Networks

Gаnchеvа, V., Jongov, T., & Georgiev, I. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-34960-7_16

Convolutional Neural Network to Classify Medical Images of Rare Brain Disorders

Saha, P., Chowdhury, S., Mehrab, A. K. M. F., & Alam, J. (2022) · International Conference on Healthcare Engineering (ICHE) · doi:10.1109/iche55634.2022.10179875

Using Deep Learning Neural Networks To Classify X-Ray Images

Si, J. (2023) · Advances in Engineering Technology Research · doi:10.56028/aetr.6.1.588.2023

Classificação de Doença Hepática Gordurosa Não Alcoólica em Imagens Térmicas usando Temporal Convolutional Networks

Farias, M. V. D. S., da Silva, I. F. S., Silva, A. C., Filho, H. M. D. A. M., & de Paiva, A. C. (2023) · Anais do XXIII Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2023) · doi:10.5753/sbcas.2023.229802

A Machine Learning Application for Medical Image Analysis Using Deep Convolutional Neural Networks (CNNs) and Transfer Learning Models for Pneumonia Detection

Shirwaikar, R. D. (2024) · Journal of Electrical Systems · doi:10.52783/jes.2591 · Cited by 2

Automatic Detection of Pneumonia from Chest X-Rays Using Deep Learning

Nath, M., & Choudhury, C. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-6315-7_14 · Cited by 12

A pneumonia classification accuracy enhancement scheme based on data augmentation, data preprocessing, and transfer learning

Mao, T., Li, T., & Zhang, Y. (2023) · International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID) · doi:10.1117/12.2674701 · Cited by 2

Pneumonia Detection using X-Ray Images with Deep Learning

Magar, H., Patil, S., Waykole, S. R., Sandikar, S. D., & Parakh, N. D. (2020) · International Journal of Computer Applications Technology and Research · doi:10.7753/ijcatr0905.1004 · Cited by 3

Pneumonia Classification Using VGG19 Transfer Learning And Data Augmentation Across Diverse Chest X-Ray Datasets

Kalaiselvi, K. (2024) · African Journal of Biomedical Research · doi:10.53555/ajbr.v27i3s.2634 · Cited by 1