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Research Article

Hybrid Multimodal Data Fusion Model for Early Parkinson’s Disease Diagnosis

  • ICCAIS-2026
  • Volume 5, Issue 1
  • Pages 98-105
  • Published Online: 2026
Open Access Peer Reviewed Crossref DOI

Authors

  • Pedina Bavishya1
  • Suvam Nahak2
  • Soumya Ranjan Mishra3
  • Sachikanta Dash4
  • Supratika Padhi5
  • Manish Pradhan6

1 2 3 5 6 Department of CSA, GIET University Gunupur, Odisha, India. 4 Madanapalle Institute of Technology and Science University, Andhra Pradesh, India.

Article Information

Organised By
Madanapalle Institute of Technology & Science (MITS)
Conference Date
9 & 10 March 2026
Pages
98-105
Article Type
Research Article
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References

1. Ali, L., He, Z., Cao, W., Rauf, H.T., Imrana, Y., Bin Heyat, M.B. MMDD-Ensemble: A Multimodal Data-Driven Ensemble Approach for Parkinson‘s Disease Detection. Frontiers in Neuroscience, 2021, 15, 754058.
2. Dadashzadeh, A., Whone, A., Rolinski, M., Mirmehdi, M. Exploring Motion Boundaries in an End-to-End Network for Vision-based Parkinson‘s Severity Assessment. arXiv preprint arXiv:2012.09890, 2020.
3. Mishra, S. R., Dash, S., Padhy, S., Kumar, N., & Dash, Y. (2024, September). Integrating Multi-Omics Data for Advanced Diabetes Prediction and Understanding. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1447-1453). IEEE.
4. Dash, S., Mishra, S. R., & Baboo, A. (2025, January). Enhancing Diabetes Prediction using Hybrid Ensemble Approach. In 2025 International Conference on Intelligent Systems and Computational Networks (ICISCN) (pp. 1-6). IEEE.
5. Egger, J., Gsaxner, C., Pepe, A., Pomykala, K.L., Jonske, F., Kurz, M., Li, J., Kleesiek, J. Medical Deep Learning-A Systematic Meta- Review. Computer Methods and Programmers in Biomedicine, 2022, 221, 106874.
6. Gazda, M., Hireš, M., Drotár, P. Multiple-Fine-Tuned Convolutional Neural Networks for Parkinson‘s Disease Diagnosis from Offline Handwriting. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 52(1), 78-89.
7. Dash, S., Mishra, S. R., & Baboo, A. (2025, January). Efficient Prediction of Diabetes Mellitus Through Hybrid Ensemble Machine Learning Model Using IoT. In 2025 1st International Conference on AIML-Applications for Engineering & Technology (ICAET) (pp. 1- 6). IEEE.
8. Mishra, S. R., & Dash, S. (2024, December). Machine Learning Based Diabetes Prediction Using the PIMA Indian Dataset. In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES) (pp. 1-6). IEEE.
9. Mishra, S. R., Dash, S., Padhy, S., & Das, R. K. (2024, September). Diabetic Foot Ulcer Diagnosis Through Deep Learning Model. In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit) (pp. 1194-1199). IEEE.
10. Goetz, C. G., Poewe, W., Rascol, O., Sampaio, C., Stebbins, G. T., Counsell, C., Giladi, N., Holloway, R. G., Moore, C. G., Wenning, G.
11. K. Movement Disorder Society Task Force Report on the Hoehn and Yahr Staging Scale: Status and Recommendations the Movement Disorder Society Task Force on Rating Scales for Parkinson‘s Disease. Movement Disorders, 2004, 19(9), 1020-1028.
12. He, B., Lu, Q., Lang, J., Yu, H., Peng, C., Bing, P., ... & Tian, G.
13. (2020). A new method for CTC images recognition based on machine learning. Frontiers in Bioengineering and Biotechnology, 8, 897.
14. Mishra, S. R., & Dash, S. (2024). Iterative Model Design for Diabetes Analysis Using FedOmics Causal Network and Federated Multi- Omics Variational Autoencoder. International Journal of Emerging Technologies and Innovative Research, 11(6).
15. Mishra, S. R., & Dash, S. (2024). Predictive Analysis On Diabetes Detection Using Pima Indian Diabetes Dataset. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), 11(2).
16. Baboo, A., Mishra, S. R., & Dash, S. (2024, November). An Improvised Diabetes Prediction System Using Hybrid Ensemble Approach. In 2024 IEEE 11th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (pp. 1-6). IEEE.
17. Huang, H., Wu, N., Liang, Y., Peng, X., & Shu, J. (2022). SLNL: A novel method for gene selection and phenotype classification. International Journal of Intelligent Systems, 37(9), 6283-6304.
18. Kumar, S. J. K., Parthasarathi, P., Hogo, M. A., Masud, M., Al-Amri,J. F., & Abouhawwash, M. (2023). Breast Cancer Detection Using Breastnet-18 Augmentation with Fine Tuned Vgg-16s Breast Cancer Detection Using Breastnet-18 Augmentation with Fine Tuned Vgg-
19. 16. Intelligent Automation & Soft Computing, 36(2).
20. Mishra, S. R., & Dash, S. (2026). AI ‐ Driven Remote Health Monitoring for Predicting Diabetes and Heart Diseases Using ULMCSO and PGND Models. Hyper ‐ Intelligent Networks: Exploring the Future of Connectivity for Society 5.0, 219-247.
21. Mishra, S. R., Dash, S., Padhy, S., & Samuel, P. (2026). Legal Aspects of Operating IoMT Applications in the Fog Computing. In Integrating Cloud, Fog, and Edge Computing in Healthcare: Federated Learning and Blockchain Approaches: Harnessing Distributed Technologies for Enhanced Healthcare Delivery (pp. 211- 224). Cham: Springer Nature Switzerland.
22. Rath, L., Mishra, S. R., Dash, S., Pradhan, P. C., & Baboo, A. (2025). Predicting diabetic patients coronary artery calcium score, deep learning using retinal images. In Intelligent Computing Techniques and Applications (pp. 113-118). CRC Press.
23. Baboo, A., Patro, S. P., & Dash, S. (2024, December). A Deep Learning Approach for Enhancing Cardiovascular Disease Prediction Using ECG Data. In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES) (pp. 1-5). IEEE.
24. Lin, Q., Xiongbo, G., Zhang, W., Cai, L., Yang, R., Chen, H., & Cai,K. (2023). A novel approach of surface texture mapping for cone- beam computed tomography in image-guided surgical navigation. IEEE Journal of Biomedical and Health Informatics.
25. Pattnayak, A. P., Mishra, S. R., Dash, S., & Baboo, A. (2025). Utilization of deep learning and machine learning models to approach high glucose and low glucose prediction with type 1 diabetes mellitus in adult patients. In Intelligent Computing Techniques and Applications (pp. 102-107). CRC Press.
26. Dora, N., Dash, S., Baboo, A., & Mishra, S. R. (2025, August). Efficient Nail Disease Diagnosis Using Deep Neural Networks for Predicting Abnormalities. In 2025 International Conference on Next Generation of Green Information and Emerging Technologies (GIET) (pp. 1-5). IEEE.
27. Mishra, S. R., Dash, S., & Rath, L. (2024, November). Effective Diabetes Mellitus Prediction Using a Hybrid Ensemble Machine Learning Model with Iot. In 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS) (pp. 1- 8). IEEE.
28. Dash, A. B., Dash, S., Padhy, S., Kumar, N., Pati, G. K., & Uthansingh, K. (2025). Leveraging inception-v3 CNN model for efficient image classification. In Intelligent Computing and Communication Techniques (pp. 341-348). CRC Press.
29. Maheswaran, S., Sathesh, S., Ajith Kumar, P., Hariharan, R. S., Chandra Sekar, P., Ridhish, R., & Gomathi, R. D. (2022, August). Yolo based efficient vigorous scene detection and blurring for harmful content management to avoid children’s destruction. In 2022 3rd International Conference on Electronics and Sustainable Communication Systems (ICESC) (pp. 1063-1073). IEEE.
30. Odusami, M., Maskeliūnas, R., Damaševičius, R., & Misra, S. (2023). Explainable deep-learning-based diagnosis of Alzheimer’s disease using multimodal input fusion of PET and MRI Images. Journal of Medical and Biological Engineering, 43(3), 291-302.
31. Khuntuli, B., Dash, S., Pradhan, P. C., & Mishra, S. R. Combating food insecurity through remote sensing and machine learning for enhanced crop yield prediction. In Intelligent Computing Techniques and Applications (pp. 135-140). CRC Press.
32. Sahu, P. K., Biswal, B. B., Mishra, S. R., Padhy, J., & Kumar, D. (2025, March). Demand-Based Secured Data Transmission in WSN. In International Conference on Next Generation Computing and Communication Applications (pp. 37-44). Cham: Springer Nature Switzerland.
33. Khuntuli, B., Dash, S., Pradhan, P. C., & Mishra, S. R. Combating food insecurity through remote sensing and machine learning for enhanced crop yield prediction. In Intelligent Computing Techniques and Applications (pp. 135-140). CRC Press.
34. Kanna, G. P., Kumar, S. J., Parthasarathi, P., & Kumar, Y. (2023). A review on prediction and prognosis of the prostate cancer and gleason grading of prostatic carcinoma using deep transfer learning based approaches. Archives of Computational Methods in Engineering, 30(5), 3113-3132.
35. Lu, S., Yang, J., Yang, B., Yin, Z., Liu, M., Yin, L., & Zheng, W. (2023). Analysis and design of surgical instrument localization algorithm. Comput. Model. Eng. Sci, 137(1), 669-685.
36. Yang, X., Ye, Q., Cai, G., Wang, Y., & Cai, G. (2022). PD-ResNet
37. for classification of Parkinson’s disease from gait. IEEE Journal of Translational Engineering in Health and Medicine, 10, 1-11.
38. Zhang, J., Shen, Q., Ma, Y., Liu, L., Jia, W., Chen, L., & Xie, J. (2022). Calcium homeostasis in Parkinson’s disease: from pathology to treatment. Neuroscience Bulletin, 38(10), 1267-1270.
39. Zhang, R., Jia, J., & Zhang, R. (2022). EEG analysis of Parkinson's disease using time–frequency analysis and deep learning. Biomedical Signal Processing and Control, 78, 103883.
40. Baboo, A., Dash, S., Padhy, S., & Samuel, P. (2026). Testing Perspectives of Fog-Based IoMT Applications with Federated Learning. In Integrating Cloud, Fog, and Edge Computing in Healthcare: Federated Learning and Blockchain Approaches: Harnessing Distributed Technologies for Enhanced Healthcare Delivery (pp. 199-210). Cham: Springer Nature Switzerland.
41. Baboo, A., Mishra, S. R., & Dash, S. (2024, November). An Improvised Diabetes Prediction System Using Hybrid Ensemble Approach. In 2024 IEEE 11th Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering (UPCON) (pp. 1-6). IEEE
42. Dash, A. B., Dash, S., Padhy, S., Mishra, B., & Paikaray, B. K. (2025). Streamlining colorectal cancer diagnosis: leveraging MobileNet-V3 for efficient image classification. Int. J. Internet Manufacturing and Services, 11(4), 317.
43. Khandakhani, S. W., Dash, S., Padhy, S., & Panda, R. (2024, December). Implementation of Customized Convolutional Neural Networks for Handwritten Marathi Character Recognition. In 2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES) (pp. 1-6). IEEE.
44. Kumar, K. D., Dash, S., Ganiya, R. K., & Pradhan, P. C. (2025). A genetic algorithm-optimized hybrid CNN-LSTM for robust EEG seizure detection and adversarial defense. In Intelligent Computing Techniques and Applications (pp. 96-101). CRC Press.
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