{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,15]],"date-time":"2025-02-15T05:15:09Z","timestamp":1739596509309,"version":"3.37.1"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T00:00:00Z","timestamp":1721001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T00:00:00Z","timestamp":1721001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Wireless Netw"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s11276-024-03807-0","type":"journal-article","created":{"date-parts":[[2024,7,15]],"date-time":"2024-07-15T12:01:42Z","timestamp":1721044902000},"page":"1129-1143","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RSO-MRSA: rat swarm optimization based modified Rivest\u2013Shamir\u2013Adleman for secure and efficient healthcare monitoring system"],"prefix":"10.1007","volume":"31","author":[{"given":"T.","family":"Sethukarasi","sequence":"first","affiliation":[]},{"given":"D.","family":"Hemavathi","sequence":"additional","affiliation":[]},{"given":"S.","family":"Swetha","sequence":"additional","affiliation":[]},{"given":"S.","family":"Samundeswari","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,15]]},"reference":[{"issue":"2","key":"3807_CR1","doi-asserted-by":"publisher","first-page":"88","DOI":"10.3390\/a16020088","volume":"16","author":"CM Bhatt","year":"2023","unstructured":"Bhatt, C. M., Patel, P., Ghetia, T., & Mazzeo, P. L. (2023). Effective heart disease prediction using machine learning techniques. Algorithms, 16(2), 88.","journal-title":"Algorithms"},{"issue":"18","key":"3807_CR2","doi-asserted-by":"publisher","first-page":"12145","DOI":"10.1007\/s00500-021-05865-4","volume":"25","author":"S Basheer","year":"2021","unstructured":"Basheer, S., Alluhaidan, A. S., & Bivi, M. A. (2021). Real-time monitoring system for early prediction of heart disease using Internet of Things. Soft Computing, 25(18), 12145\u201312158.","journal-title":"Soft Computing"},{"key":"3807_CR3","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1016\/j.inffus.2020.06.008","volume":"63","author":"F Ali","year":"2020","unstructured":"Ali, F., El-Sappagh, S., Islam, S. R., Kwak, D., Ali, A., Imran, M., & Kwak, K. S. (2020). A smart healthcare monitoring system for heart disease prediction based on ensemble deep learning and feature fusion. Information Fusion, 63, 208\u2013222.","journal-title":"Information Fusion"},{"key":"3807_CR4","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.future.2019.10.043","volume":"104","author":"S Tuli","year":"2020","unstructured":"Tuli, S., Basumatary, N., Gill, S. S., Kahani, M., Arya, R. C., Wander, G. S., & Buyya, R. (2020). HealthFog: An ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated IoT and fog computing environments. Future Generation Computer Systems, 104, 187\u2013200.","journal-title":"Future Generation Computer Systems"},{"key":"3807_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119859","volume":"223","author":"A Jain","year":"2023","unstructured":"Jain, A., Rao, A. C. S., Jain, P. K., & Hu, Y. C. (2023). Optimized levy flight model for heart disease prediction using CNN framework in big data application. Expert Systems with Applications, 223, 119859.","journal-title":"Expert Systems with Applications"},{"issue":"23","key":"3807_CR6","doi-asserted-by":"publisher","first-page":"16921","DOI":"10.1109\/JIOT.2021.3053420","volume":"8","author":"YS Su","year":"2021","unstructured":"Su, Y. S., Ding, T. J., & Chen, M. Y. (2021). Deep learning methods in internet of medical things for valvular heart disease screening system. IEEE Internet of Things Journal, 8(23), 16921\u201316932.","journal-title":"IEEE Internet of Things Journal"},{"key":"3807_CR7","doi-asserted-by":"publisher","first-page":"122259","DOI":"10.1109\/ACCESS.2020.3006424","volume":"8","author":"MA Khan","year":"2020","unstructured":"Khan, M. A., & Algarni, F. (2020). A healthcare monitoring system for the diagnosis of heart disease in the IoMT cloud environment using MSSO-ANFIS. IEEE Access, 8, 122259\u2013122269.","journal-title":"IEEE Access"},{"issue":"22","key":"3807_CR8","doi-asserted-by":"publisher","first-page":"17111","DOI":"10.1007\/s00500-020-05003-6","volume":"24","author":"A Souri","year":"2020","unstructured":"Souri, A., Ghafour, M. Y., Ahmed, A. M., Safara, F., Yamini, A., & Hoseyninezhad, M. (2020). A new machine learning-based healthcare monitoring model for student\u2019s condition diagnosis in Internet of Things environment. Soft Computing, 24(22), 17111\u201317121.","journal-title":"Soft Computing"},{"key":"3807_CR9","doi-asserted-by":"crossref","unstructured":"Nguyen, T. H., Nguyen, T .N. & Nguyen, T. T. (2020). A deep learning framework for heart disease classification in an IoTs-based system.\u00a0A Handbook of Internet of Things in Biomedical and Cyber Physical System, pp.217\u2013244.","DOI":"10.1007\/978-3-030-23983-1_9"},{"key":"3807_CR10","doi-asserted-by":"publisher","first-page":"9977","DOI":"10.1007\/s11042-019-07742-7","volume":"79","author":"M Abdel-Basset","year":"2020","unstructured":"Abdel-Basset, M., Gamal, A., Manogaran, G., Son, L. H., & Long, H. V. (2020). A novel group decision making model based on neutrosophic sets for heart disease diagnosis. Multimedia Tools and Applications, 79, 9977\u201310002.","journal-title":"Multimedia Tools and Applications"},{"key":"3807_CR11","doi-asserted-by":"publisher","first-page":"135784","DOI":"10.1109\/ACCESS.2020.3007561","volume":"8","author":"SS Sarmah","year":"2020","unstructured":"Sarmah, S. S. (2020). An efficient IoT-based patient monitoring and heart disease prediction system using deep learning modified neural network. IEEE access, 8, 135784\u2013135797.","journal-title":"IEEE access"},{"key":"3807_CR12","doi-asserted-by":"publisher","first-page":"180235","DOI":"10.1109\/ACCESS.2019.2952107","volume":"7","author":"A Javeed","year":"2019","unstructured":"Javeed, A., Zhou, S., Yongjian, L., Qasim, I., Noor, A., & Nour, R. (2019). An intelligent learning system based on random search algorithm and optimized random forest model for improved heart disease detection. IEEE access, 7, 180235\u2013180243.","journal-title":"IEEE access"},{"key":"3807_CR13","doi-asserted-by":"publisher","first-page":"34717","DOI":"10.1109\/ACCESS.2020.2974687","volume":"8","author":"MA Khan","year":"2020","unstructured":"Khan, M. A. (2020). An IoT framework for heart disease prediction based on MDCNN classifier. IEEE Access, 8, 34717\u201334727.","journal-title":"IEEE Access"},{"key":"3807_CR14","doi-asserted-by":"publisher","first-page":"7979","DOI":"10.1007\/s00521-020-05542-x","volume":"33","author":"S Dami","year":"2021","unstructured":"Dami, S., & Yahaghizadeh, M. (2021). Predicting cardiovascular events with deep learning approach in the context of the internet of things. Neural Computing and Applications, 33, 7979\u20137996.","journal-title":"Neural Computing and Applications"},{"issue":"20","key":"3807_CR15","doi-asserted-by":"publisher","first-page":"14723","DOI":"10.1007\/s00521-021-06124-1","volume":"35","author":"S Nandy","year":"2023","unstructured":"Nandy, S., Adhikari, M., Balasubramanian, V., Menon, V. G., Li, X., & Zakarya, M. (2023). An intelligent heart disease prediction system based on swarm-artificial neural network. Neural Computing and Applications, 35(20), 14723\u201314737.","journal-title":"Neural Computing and Applications"},{"key":"3807_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.07.043","volume":"147","author":"Z Al-Makhadmeh","year":"2019","unstructured":"Al-Makhadmeh, Z., & Tolba, A. (2019). Utilizing IoT wearable medical device for heart disease prediction using higher order Boltzmann model: A classification approach. Measurement, 147, 106815.","journal-title":"Measurement"},{"key":"3807_CR17","doi-asserted-by":"publisher","first-page":"14777","DOI":"10.1007\/s10586-018-2416-4","volume":"22","author":"CB Gokulnath","year":"2019","unstructured":"Gokulnath, C. B., & Shantharajah, S. P. (2019). An optimized feature selection based on genetic approach and support vector machine for heart disease. Cluster Computing, 22, 14777\u201314787.","journal-title":"Cluster Computing"},{"key":"3807_CR18","doi-asserted-by":"crossref","unstructured":"Khourdifi, Y. & Baha, M. (2019). Heart disease prediction and classification using machine learning algorithms optimized by particle swarm optimization and ant colony optimization.\u00a0International Journal of Intelligent Engineering and Systems,\u00a012(1).","DOI":"10.22266\/ijies2019.0228.24"},{"issue":"1","key":"3807_CR19","first-page":"530","volume":"10","author":"YK Kumar","year":"2020","unstructured":"Kumar, Y. K., & Shafi, R. M. (2020). An efficient and secure data storage in cloud computing using modified RSA public key cryptosystem. International Journal of Electrical and Computer Engineering, 10(1), 530.","journal-title":"International Journal of Electrical and Computer Engineering"},{"key":"3807_CR20","unstructured":"Khan, M. A. R., Rahman, M., Salehin, J. U., Islam, M. S. & Rabbi, M. F. (2021). Efficient data mining techniques for heart disease prediction and comparative analysis of classification algorithms."},{"key":"3807_CR21","doi-asserted-by":"publisher","first-page":"96946","DOI":"10.1109\/ACCESS.2020.2993536","volume":"8","author":"J Zheng","year":"2020","unstructured":"Zheng, J., Lin, D., Gao, Z., Wang, S., He, M., & Fan, J. (2020). Deep learning assisted efficient AdaBoost algorithm for breast cancer detection and early diagnosis. IEEE Access, 8, 96946\u201396954.","journal-title":"IEEE Access"},{"key":"3807_CR22","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1016\/j.ins.2021.06.009","volume":"574","author":"J Wang","year":"2021","unstructured":"Wang, J. (2021). An intelligent computer-aided approach for atrial fibrillation and atrial flutter signals classification using modified bidirectional LSTM network. Information Sciences, 574, 320\u2013332.","journal-title":"Information Sciences"},{"key":"3807_CR23","doi-asserted-by":"publisher","first-page":"8457","DOI":"10.1007\/s12652-020-02580-0","volume":"12","author":"G Dhiman","year":"2021","unstructured":"Dhiman, G., Garg, M., Nagar, A., Kumar, V., & Dehghani, M. (2021). A novel algorithm for global optimization: Rat swarm optimizer. Journal of Ambient Intelligence and Humanized Computing, 12, 8457\u20138482.","journal-title":"Journal of Ambient Intelligence and Humanized Computing"},{"key":"3807_CR24","unstructured":"https:\/\/www.kaggle.com\/datasets\/sid321axn\/heart-statlog-cleveland-hungary-final"}],"container-title":["Wireless Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-024-03807-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11276-024-03807-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-024-03807-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,14]],"date-time":"2025-02-14T12:14:57Z","timestamp":1739535297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11276-024-03807-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,15]]},"references-count":24,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["3807"],"URL":"https:\/\/doi.org\/10.1007\/s11276-024-03807-0","relation":{},"ISSN":["1022-0038","1572-8196"],"issn-type":[{"type":"print","value":"1022-0038"},{"type":"electronic","value":"1572-8196"}],"subject":[],"published":{"date-parts":[[2024,7,15]]},"assertion":[{"value":"19 June 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 July 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human or animal subjects performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}