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Optimized Deep learning Frameworks for the Medical Image Transmission in IoMT Environment Cover

Optimized Deep learning Frameworks for the Medical Image Transmission in IoMT Environment

By: Rashmi P and  R. Gomathi  
Open Access
|Feb 2025

References

  1. Wazid, Mohammad, and Prosanta Gope. "BACKM-EHA: A novel blockchain-enabled security solution for IoMT-based e-healthcare applications." ACM Transactions on Internet Technology 23.3 (2023): 1-28.
  2. Muhammad, Ghulam, et al. "A comprehensive survey on multimodal medical signals fusion for smart healthcare systems." Information Fusion 76 (2021): 355-375.
  3. Ghazal, Taher M., et al. "Secure IoMT pattern recognition and exploitation for multimedia information processing using private blockchain and fuzzy logic." Transactions on Asian and Low-Resource Language Information Processing (2022).
  4. R R, Rajalaxmi & Prasad, L.V. & Janakiramaiah, B. & Pavankumar, C.S. & Neelima, N. & Veerappampalayam Easwaramoorthy, Sathishkumar. (2022). Optimizing Hyperparameters and Performance Analysis of LSTM Model in Detecting Fake News on Social media. ACM Transactions on Asian and Low-Resource Language Information Processing. 10.1145/3511897.
  5. Gkelios, Socratis & Features, Deep & Plakias, Spiros & Boutalis, Yiannis & Chatzichristofis, Savvas. (2021). Deep Convolutional Features for Image Retrieval. Expert Systems with Applications. 177. 114940. 10.1016/j.eswa.2021.114940.
  6. Peng, Yitao & He, Lianghua & Hu, Die & Liu, Yihang & Yang, Longzhen & Shang, Shaohua. (2024). Decoupling Deep Learning for Enhanced Image Recognition Interpretability. ACM Transactions on Multimedia Computing, Communications, and Applications. 20. 10.1145/3674837.
  7. Elsayed Abd Elaziz, Mohamed & Mabrouk, Alhassan & Dahou, Abdelghani & Aaaa, Samo. (2022). Medical Image Classification Utilizing Ensemble Learning and Levy Flight-Based Honey Badger Algorithm on 6G-Enabled Internet of Things. Computational Intelligence and Neuroscience. 2022. 1-17. 10.1155/2022/5830766.
  8. Hosseinzadeh, Mehdi & Ahmed, Omed & Ghafour, Marwan & Safara, Fatemeh & Ali, Saqib & Vo, Bay & Chiang, Hsiu-Sen. (2021). A multiple multilayer perceptron neural network with an adaptive learning algorithm for thyroid disease diagnosis in the internet of medical things. The Journal of Supercomputing. 77. 10.1007/s11227-020-03404-w.
  9. Khamparia, Aditya & Singh, Prakash & Rani, Poonam & Samanta, Debabrata & Khanna, Ashish & Bhushan, Bharat. (2021). An internet of health things‐driven deep learning framework for detection and classification of skin cancer using transfer learning. Transactions on Emerging Telecommunications Technologies. 32. 10.1002/ett.3963.
  10. Balhareth, G.; Ilyas, M. Optimized Intrusion Detection for IoMT Networks with Tree-Based Machine Learning and Filter-Based Feature Selection. Sensors 2024, 24, 5712. https://doi.org/10.3390/s24175712
  11. Rahman, A., Debnath, T., Kundu, D., Khan, M. S. I., Aishi, A. A., Sazzad, S., Sayduzzaman, M., & Band, S. S. (2024). Machine learning and deep learning-based approach in smart healthcare: Recent advances, applications, challenges and opportunities. Public Health, 11(1), 58-109. https://doi.org/10.3934/publichealth.2024004
  12. Nandagopal, M., Seerangan, K., Govindaraju, T. et al. A Deep Auto-Optimized Collaborative Learning (DACL) model for disease prognosis using AI-IoMT systems. Sci Rep 14, 10280 (2024). https://doi.org/10.1038/s41598-024-59846-2
  13. Datta Gupta, K., Sharma, D.K., Ahmed, S. et al. A Novel Lightweight Deep Learning-Based Histopathological Image Classification Model for IoMT. Neural Process Lett 55, 205–228 (2023). https://doi.org/10.1007/s11063-021-10555-1.
  14. Lata, K.; Cenkeramaddi, L.R. Deep Learning for Medical Image Cryptography: A Comprehensive Review. Appl. Sci. 2023, 13, 8295. https://doi.org/10.3390/app13148295.
  15. Thimmapuram, Madhuri & Salvadi, Shoba & Pallati, Narsimhulu & Aluvalu, Rajanikanth. (2023). Medical Image Classification Using DL-based Feature Extraction in IoMT. Recent Patents on Engineering. 17. 10.2174/1872212117666230222093128.
  16. Li M, Jiang Y, Zhang Y, Zhu H. Medical image analysis using deep learning algorithms. Front Public Health. 2023 Nov 7;11:1273253. doi: 10.3389/fpubh.2023.1273253. PMID: 38026291; PMCID: PMC10662291.
  17. Arti Tiwari and Millie Pant. 2022. Optimized Deep-Neural Network for Content-based Medical Image Retrieval in a Brownfield IoMT Network. ACM Trans. Multimedia Comput. Commun. Appl. 18, 2s, Article 125 (June 2022), 26 pages. https://doi.org/10.1145/3546194
  18. Balaji, P., Sri Revathi, B., Gobinathan, P., Shamsudheen, S., & Vaiyapuri, T. (2022). Optimal IoT based improved deep learning model for medical image classification. Computers, Materials & Continua. https://doi.org/10.32604/cmc.2022.028560
  19. T. Zhang et al., "A Joint Deep Learning and Internet of Medical Things Driven Framework for Elderly Patients," in IEEE Access, vol. 8, pp. 75822-75832, 2020, doi: 10.1109/ACCESS.2020.2989143
  20. Ogundokun, Roseline & Misra, Sanjay & Douglas, Mychal & Damaševičius, Robertas & Maskeliunas, Rytis. (2022). Medical Internet-of-Things Based Breast Cancer Diagnosis Using Hyperparameter-Optimized Neural Networks. Future Internet. 14. 153. 10.3390/fi14050153.
  21. Cooney, Ciaran & Korik, Attila & Folli, Raffaella & Coyle, Damien. (2020). Evaluation of Hyperparameter Optimization in Machine and Deep Learning Methods for Decoding Imagined Speech EEG. Sensors. 20. 4629. 10.3390/s20164629.
  22. Memon, Muhammad & Li, Jian & Haq, Amin & Memon, Muhammad & Zhou, Wang. (2019). Breast Cancer Detection in the IOT Health Environment Using Modified Recursive Feature Selection. International Journal of Wireless and Mobile Computing. 2019. 10.1155/2019/5176705.
Language: English
Page range: 148 - 165
Submitted on: Sep 20, 2024
Accepted on: Oct 28, 2024
Published on: Feb 24, 2025
Published by: Future Sciences For Digital Publishing
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2025 Rashmi P, R. Gomathi, published by Future Sciences For Digital Publishing
This work is licensed under the Creative Commons Attribution 4.0 License.