A Review on Multiple-Ocular Disease Detection Methodology using ML and DL Techniques
DOI:
https://doi.org/10.32628/CSEIT2410588Keywords:
Ocular Diseases, Machine Learning, Deep Learning, Convolutional Neural Networks, Attention Mechanisms, Fundus Images, Disease ClassificationAbstract
The rapid advancement in machine learning (ML) and deep learning (DL) techniques has significantly impacted the detection and diagnosis of ocular diseases, which are critical for preserving vision and overall eye health. This review aims to explore the various ML and DL methodologies applied to the detection of multiple ocular diseases, highlighting their effectiveness, limitations, and areas for improvement. The motivation behind this review stems from the increasing prevalence of ocular diseases and the need for efficient, accurate diagnostic tools. Despite the promising results of existing techniques, limitations such as data variability, the need for extensive training data, and computational resource requirements persist. The objective is to synthesize current methodologies and propose enhancements, particularly through the integration of attention mechanisms in convolutional neural networks (CNNs). This review identifies gaps in current research and suggests directions for future work to enhance diagnostic accuracy and clinical applicability.
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Deepak, G. Divya, and Subraya Krishna Bhat. “Deep Learning-Based CNN for Multiclassification of Ocular Diseases Using Transfer Learning.” Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, vol. 12, no. 1, 2024, https://doi.org/10.1080/21681163.2024.2335959. DOI: https://doi.org/10.1080/21681163.2024.2335959
Al-Fahdawi, Shumoos, et al. “Fundus-DeepNet: Multi-Label Deep Learning Classification System for Enhanced Detection of Multiple Ocular Diseases through Data Fusion of Fundus Images.” Information Fusion, vol. 102, no. July 2023, 2024, p. 102059, https://doi.org/10.1016/j.inffus.2023.102059. DOI: https://doi.org/10.1016/j.inffus.2023.102059
Santone, Antonella, et al. “A Method for Ocular Disease Diagnosis through Visual Prediction Explainability.” Electronics, vol. 13, no. 14, 2024, p. 2706, https://doi.org/10.3390/electronics13142706. DOI: https://doi.org/10.3390/electronics13142706
Veena, K. M., et al. “FFA-Lens: Lesion Detection Tool for Chronic Ocular Diseases in Fluorescein Angiography Images.” SoftwareX, vol. 26, 2024, p. 101646, https://doi.org/10.1016/j.softx.2024.101646. DOI: https://doi.org/10.1016/j.softx.2024.101646
ÇETİNER, Halit. “Cataract Disease Classification from Fundus Images with Transfer Learning Based Deep Learning Model on Two Ocular Disease Datasets.” Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 13, 2023, pp. 256–69, https://doi.org/10.17714/gumusfenbil.1168842. DOI: https://doi.org/10.17714/gumusfenbil.1168842
Böhm, Elsa Wilma, et al. “Oxidative Stress in the Eye and Its Role in the Pathophysiology of Ocular Diseases.” Redox Biology, vol. 68, no. November, 2023, https://doi.org/10.1016/j.redox.2023.102967. DOI: https://doi.org/10.1016/j.redox.2023.102967
Vadduri, Maneesha, and P. Kuppusamy. “Enhancing Ocular Healthcare: Deep Learning-Based Multi-Class Diabetic Eye Disease Segmentation and Classification.” IEEE Access, vol. 11, no. November, 2023, pp. 137881–98, https://doi.org/10.1109/ACCESS.2023.3339574. DOI: https://doi.org/10.1109/ACCESS.2023.3339574
Mayya, Veena, et al. “An Empirical Study of Preprocessing Techniques with Convolutional Neural Networks for Accurate Detection of Chronic Ocular Diseases Using Fundus Images.” Applied Intelligence, vol. 53, no. 2, 2023, pp. 1548–66, https://doi.org/10.1007/s10489-022-03490-8. DOI: https://doi.org/10.1007/s10489-022-03490-8
Tanvir, Kazi, et al. “Clinical Insights through Xception: A Multiclass Classification of Ocular Pathologies.” Article in Tuijin Jishu/Journal of Propulsion Technology, vol. 44, no. 04, 2023, pp. 5876–85, https://www.researchgate.net/publication/375758282.
Kaewboonma, Nattapong, et al. “Thai Rubber Leaf Disease Classification Using Deep Learning Techniques.” ACM International Conference Proceeding Series, 2023, pp. 84–91, https://doi.org/10.1145/3639592.3639605. DOI: https://doi.org/10.1145/3639592.3639605
Tan, Yuhe, and Xufang Sun. “Ocular Images-Based Artificial Intelligence on Systemic Diseases.” BioMedical Engineering Online, vol. 22, no. 1, 2023, pp. 1–14, https://doi.org/10.1186/s12938-023-01110-1. DOI: https://doi.org/10.1186/s12938-023-01110-1
Huang, Xuan, et al. “GABNet: Global Attention Block for Retinal OCT Disease Classification.” Frontiers in Neuroscience, vol. 17, 2023, https://doi.org/10.3389/fnins.2023.1143422. DOI: https://doi.org/10.3389/fnins.2023.1143422
Zhang, Zuhui, et al. “Artificial Intelligence-Assisted Diagnosis of Ocular Surface Diseases.” Frontiers in Cell and Developmental Biology, vol. 11, no. February, 2023, pp. 1–19, https://doi.org/10.3389/fcell.2023.1133680. DOI: https://doi.org/10.3389/fcell.2023.1133680
Wang, Qiong, et al. “Two-Stage Cross-Domain Ocular Disease Recognition With Data Augmentation.” IEEE Access, vol. 11, no. October, 2023, pp. 114725–31, https://doi.org/10.1109/ACCESS.2023.3324401. DOI: https://doi.org/10.1109/ACCESS.2023.3324401
Bhavesh Kataria, Dr. Harikrishna B. Jethva (2020). Sanskrit Character Recognition using Convolutional Neural Networks : A Survey. International Journal of Advanced Science and Technology, 29(7), 1059 – 1071, May 2020. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/15068
Bhati, Amit, et al. “Discriminative Kernel Convolution Network for Multi-Label Ophthalmic Disease Detection on Imbalanced Fundus Image Dataset.” Computers in Biology and Medicine, vol. 153, 2023, pp. 1–8, https://doi.org/10.1016/j.compbiomed.2022.106519. DOI: https://doi.org/10.1016/j.compbiomed.2022.106519
Degadwala, S., et al. “Improvements in Diagnosing Kawasaki Disease Using Machine Learning Algorithms.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 7–10, https://doi.org/10.1109/ICPCSN62568.2024.00009. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00009
Mistry, S., and S. Degadwala. “Improved Multi-Type Vehicle Recognition with a Customized YOLO.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 361–65, https://doi.org/10.1109/ICPCSN62568.2024.00063. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00063
Patel, V., and S. Degadwala. “Deployment of 3D-Conv-LSTM for Precipitation Nowcast via Satellite Data.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 984–88, https://doi.org/10.1109/ICPCSN62568.2024.00164. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00164
Jagani, D., and S. Degadwala. “Monkeypox Skin Lesion Classification Using Fine-Tune CNN Model.” 2024 4th International Conference on Pervasive Computing and Social Networking (ICPCSN), 2024, pp. 37–41, https://doi.org/10.1109/ICPCSN62568.2024.00014. DOI: https://doi.org/10.1109/ICPCSN62568.2024.00014
Degadwala, Sheshang, et al. “DeepSpine: Multi-Class Spine X-Ray Conditions Classification Using Deep Learning.” Proceedings - 2024 3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024, 2024, pp. 8–13, https://doi.org/10.1109/ICSADL61749.2024.00008. DOI: https://doi.org/10.1109/ICSADL61749.2024.00008
Gadhiya, Niravkumar, et al. “Novel Approach for Data Encryption with Multilevel Compressive.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1368–72, https://doi.org/10.1109/ICICT60155.2024.10544502. DOI: https://doi.org/10.1109/ICICT60155.2024.10544502
Krishnamurthy, Vinay Nagarad Dasavandi, et al. “Predicting Hydrogen Fuel Cell Capacity Using Supervised Learning Models.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1934–38, https://doi.org/10.1109/ICICT60155.2024.10544401. DOI: https://doi.org/10.1109/ICICT60155.2024.10544401
Gadhiya, Niravkumar, et al. “A Review on Different Level Data Encryption through a Compression Techniques.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1378–81, https://doi.org/10.1109/ICICT60155.2024.10544803. DOI: https://doi.org/10.1109/ICICT60155.2024.10544803
Chakraborty, Utsho, et al. “Safeguarding Authenticity in Text with BERT-Powered Detection of AI-Generated Content.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 34–37, https://doi.org/10.1109/ICICT60155.2024.10544590. DOI: https://doi.org/10.1109/ICICT60155.2024.10544590
Prajapati, Piyush M., et al. “Exploring Methods of Mitigation against DDoS Attack in an IoT Network.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 1373–77, https://doi.org/10.1109/ICICT60155.2024.10544424. DOI: https://doi.org/10.1109/ICICT60155.2024.10544424
Agarwal, Ruhi Himanshu, et al. “Predictive Modeling for Thyroid Disease Diagnosis Using Machine Learning.” 7th International Conference on Inventive Computation Technologies, ICICT 2024, 2024, pp. 227–31, https://doi.org/10.1109/ICICT60155.2024.10544462. DOI: https://doi.org/10.1109/ICICT60155.2024.10544462
Soni, Deepika, et al. “Veterinary Medical Records Application Using AWS.” Proceedings - 2024 5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024, 2024, pp. 578–84, https://doi.org/10.1109/ICMCSI61536.2024.00091. DOI: https://doi.org/10.1109/ICMCSI61536.2024.00091
Degadwala, Sheshang, et al. “Unveiling Cholera Patterns through Machine Learning Regression for Precise Forecasting.” Proceedings - 2024 5th International Conference on Mobile Computing and Sustainable Informatics, ICMCSI 2024, 2024, pp. 39–44, https://doi.org/10.1109/ICMCSI61536.2024.00012. DOI: https://doi.org/10.1109/ICMCSI61536.2024.00012
Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Indian Language Manuscripts using Convolutional Neural Networks. Design Engineering, 2021(3), 894-911. doi : https://doi.org/10.17762/de.v2021i3.7789 DOI: https://doi.org/10.17762/de.v2021i3.7789
Pandya, D. D., et al. “Retraction: Diagnostic Criteria for Depression Based on Both Static and Dynamic Visual Features (IDCIoT 2023 - International Conference on Intelligent Data Communication Technologies and Internet of Things, Proceedings (2023) DOI: 10.1109/IDCIoT56793.2023.10053450).” IDCIoT 2023 - International Conference on Intelligent Data Communication Technologies and Internet of Things, Proceedings, 2023, p. 1, https://doi.org/10.1109/IDCIoT56793.2023.10554339. DOI: https://doi.org/10.1109/IDCIoT56793.2023.10053450
Mewada, Shubbh, et al. “Improved CAD Classification with Ensemble Classifier and Attribute Elimination.” Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 238–43, https://doi.org/10.1109/ICUIS60567.2023.00048. DOI: https://doi.org/10.1109/ICUIS60567.2023.00048
Pandya, Darshanaben D., et al. “Advancements in Multiple Sclerosis Disease Classification Through Machine Learning.” Proceedings - 2023 3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023, 2023, pp. 64–69, https://doi.org/10.1109/ICUIS60567.2023.00019. DOI: https://doi.org/10.1109/ICUIS60567.2023.00019
Degadwala, Sheshang, et al. “Enhancing Fleet Management with ESP8266-Based IoT Sensors for Weight and Location Tracking.” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, 2023, pp. 13–17, https://doi.org/10.1109/ICIMIA60377.2023.10425949. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425949
Degadwala, Sheshang, et al. “Enhancing Mesothelioma Cancer Diagnosis through Ensemble Learning Techniques.” 3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023 - Proceedings, 2023, pp. 628–32, https://doi.org/10.1109/ICIMIA60377.2023.10425887. DOI: https://doi.org/10.1109/ICIMIA60377.2023.10425887
Degadwala, Sheshang, et al. “Methods of Transfer Learning for Multiclass Hair Disease Categorization.” 2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023 - Proceedings, 2023, pp. 612–16, https://doi.org/10.1109/ICACRS58579.2023.10404492. DOI: https://doi.org/10.1109/ICACRS58579.2023.10404492
Degadwala, Sheshang, et al. “DeepTread: Exploring Transfer Learning in Tyre Quality Classification.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 1448–53, https://doi.org/10.1109/ICSCNA58489.2023.10370168. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370168
Mewada, Shubbh, et al. “Enhancing Raga Identification in Indian Classical Music with FCN-Based Models.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 980–85, https://doi.org/10.1109/ICSCNA58489.2023.10370046. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370046
Degadwala, Sheshang, et al. “Revolutionizing Hops Plant Disease Classification: Harnessing the Power of Transfer Learning.” International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, 2023, pp. 1706–11, https://doi.org/10.1109/ICSCNA58489.2023.10370692. DOI: https://doi.org/10.1109/ICSCNA58489.2023.10370692
Degadwala, Sheshang, et al. “Crime Pattern Analysis and Prediction Using Regression Models.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 771–76, https://doi.org/10.1109/ICSSAS57918.2023.10331747. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331747
Bhavesh Kataria, Dr. Harikrishna B. Jethva, "CNN-Bidirectional LSTM Based Optical Character Recognition of Sanskrit Manuscripts : A Comprehensive Systematic Literature Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology , ISSN : 2456-3307, Volume 5, Issue 2, pp.1362-1383, March-April-2019. Available at doi : https://doi.org/10.32628/cseit2064126 DOI: https://doi.org/10.32628/CSEIT2064126
Prajapati, Rohit, et al. “QoS Based Virtual Machine Consolidation for Energy Efficient and Economic Utilization of Cloud Resources.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 951–57, https://doi.org/10.1109/ICSSAS57918.2023.10331674. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331674
Patel, Fagun, et al. “Recognition of Pistachio Species with Transfer Learning Models.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 250–55, https://doi.org/10.1109/ICSSAS57918.2023.10331907. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331907
Patel, Fagun, et al. “Exploring Transfer Learning Models for Multi-Class Classification of Infected Date Palm Leaves.” International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023 - Proceedings, 2023, pp. 307–12, https://doi.org/10.1109/ICSSAS57918.2023.10331746. DOI: https://doi.org/10.1109/ICSSAS57918.2023.10331746
Pandya, Darshanaben D., et al. “Advancing Erythemato-Squamous Disease Classification with Multi-Class Machine Learning.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 542–47, https://doi.org/10.1109/I-SMAC58438.2023.10290599. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290599
Degadwala, Sheshang, et al. “Determine the Degree of Malignancy in Breast Cancer Using Machine Learning.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 483–87, https://doi.org/10.1109/I-SMAC58438.2023.10290430. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290430
Bhavesh Kataria, Dr. Harikrishna B. Jethva (2021). Optical Character Recognition of Sanskrit Manuscripts Using Convolution Neural Networks, Webology, ISSN: 1735-188X, Volume 18 Issue 5, October-2021, pp. 403-424. Available at https://www.webology.org/abstract.php?id=1681
Pandya, Darshanaben D., et al. “Unveiling the Power of Collective Intelligence: A Voting-Based Approach for Dementia Classification.” 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023 - Proceedings, 2023, pp. 478–82, https://doi.org/10.1109/I-SMAC58438.2023.10290165. DOI: https://doi.org/10.1109/I-SMAC58438.2023.10290165
Patel, Ankur, et al. “Enhancing Traffic Management with YOLOv5-Based Ambulance Tracking System.” Canadian Conference on Electrical and Computer Engineering, vol. 2023-September, 2023, pp. 528–32, https://doi.org/10.1109/CCECE58730.2023.10288751. DOI: https://doi.org/10.1109/CCECE58730.2023.10288751
Bhavesh Kataria Dr. Harikrishna B. Jethva, " Review of Advances in Digital Recognition of Indian Language Manuscripts, International Journal of Scientific Research in Science, Engineering and Technology, Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.1302-1318, January-February-2018. Available at doi : https://doi.org/10.32628/ijsrset1841215 DOI: https://doi.org/10.32628/IJSRSET1841215
Degadwala, Sheshang, et al. “Revolutionizing Prostate Cancer Diagnosis: Harnessing the Potential of Transfer Learning for MRI-Based Classification.” Proceedings of the 4th International Conference on Smart Electronics and Communication, ICOSEC 2023, 2023, pp. 938–43, https://doi.org/10.1109/ICOSEC58147.2023.10275879. DOI: https://doi.org/10.1109/ICOSEC58147.2023.10275879
Patel, Krunal, et al. “Safety Helmet Detection Using YOLO V8.” Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 22–26, https://doi.org/10.1109/ICPCSN58827.2023.00012. DOI: https://doi.org/10.1109/ICPCSN58827.2023.00012
Mehta, Jay N., et al. “EEG Brainwave Data Classification of a Confused Student Using Moving Average Feature.” Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, 2023, pp. 1461–66, https://doi.org/10.1109/ICPCSN58827.2023.00243. DOI: https://doi.org/10.1109/ICPCSN58827.2023.00243
Pareek, Naveen Kumar, et al. “Prediction of CKD Using Expert System Fuzzy Logic & AI.” Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023, 2023, pp. 103–08, https://doi.org/10.1109/ICAISS58487.2023.10250477. DOI: https://doi.org/10.1109/ICAISS58487.2023.10250477
Degadwala, Sheshang, et al. “Enhancing Prostate Cancer Diagnosis: Leveraging XGBoost for Accurate Classification.” Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems, ICAISS 2023, 2023, pp. 1776–81, https://doi.org/10.1109/ICAISS58487.2023.10250511. DOI: https://doi.org/10.1109/ICAISS58487.2023.10250511
Degadwala, Sheshang, et al. “Empowering Maxillofacial Diagnosis Through Transfer Learning Models.” Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 728–32, https://doi.org/10.1109/ICIRCA57980.2023.10220830. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220830
Degadwala, Sheshang, et al. “Enhancing Alzheimer Stage Classification of MRI Images through Transfer Learning.” Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, 2023, pp. 733–37, https://doi.org/10.1109/ICIRCA57980.2023.10220651. DOI: https://doi.org/10.1109/ICIRCA57980.2023.10220651
Degadwala, Sheshang, et al. “Optimizing Hindi Paragraph Summarization through PageRank Method.” Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, 2023, pp. 504–09, https://doi.org/10.1109/ICECAA58104.2023.10212107. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212107
Dasavandi Krishnamurthy, Vinay Nagarad, et al. “Forecasting Future Sea Level Rise: A Data-Driven Approach Using Climate Analysis.” Proceedings of the 2nd International Conference on Edge Computing and Applications, ICECAA 2023, 2023, pp. 646–51, https://doi.org/10.1109/ICECAA58104.2023.10212399. DOI: https://doi.org/10.1109/ICECAA58104.2023.10212399
Degadwala, Sheshang, et al. “Cancer Death Cases Forecasting Using Supervised Machine Learning.” 2023 4th International Conference on Electronics and Sustainable Communication Systems, ICESC 2023 - Proceedings, 2023, pp. 903–07, https://doi.org/10.1109/ICESC57686.2023.10193685. DOI: https://doi.org/10.1109/ICESC57686.2023.10193685
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