SURVEY ARTICLE
Cloud healthcare services: A comprehensive and systematic literature review
Morteza Rahimi,
Nima Jafari Navimipour,
Mehdi Hosseinzadeh,
Mohammad Hossein Moattar,
Aso Darwesh,
Morteza Rahimi
Department of Computer Engineering, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran
Search for more papers by this authorCorresponding Author
Nima Jafari Navimipour
Department of Computer Engineering, Kadir Has University, Istanbul, Turkey
Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Correspondence
Nima Jafari Navimipour, Department of Computer Engineering, Kadir Has University, Istanbul, Turkey.
Email: [email protected], [email protected]
Mehdi Hosseinzadeh, Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeonggu, Seongnam 13120, Republic of Korea.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Mehdi Hosseinzadeh
Pattern Recognition and Machine Learning Lab, Gachon University, Seongnam, Republic of Korea
Correspondence
Nima Jafari Navimipour, Department of Computer Engineering, Kadir Has University, Istanbul, Turkey.
Email: [email protected], [email protected]
Mehdi Hosseinzadeh, Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeonggu, Seongnam 13120, Republic of Korea.
Email: [email protected]
Search for more papers by this authorMohammad Hossein Moattar
Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Search for more papers by this authorAso Darwesh
Information Technology Department, University of Human Development, Sulaymaniyah, Iraq
Search for more papers by this authorMorteza Rahimi,
Nima Jafari Navimipour,
Mehdi Hosseinzadeh,
Mohammad Hossein Moattar,
Aso Darwesh,
Morteza Rahimi
Department of Computer Engineering, Sabzevar Branch, Islamic Azad University, Sabzevar, Iran
Search for more papers by this authorCorresponding Author
Nima Jafari Navimipour
Department of Computer Engineering, Kadir Has University, Istanbul, Turkey
Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
Correspondence
Nima Jafari Navimipour, Department of Computer Engineering, Kadir Has University, Istanbul, Turkey.
Email: [email protected], [email protected]
Mehdi Hosseinzadeh, Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeonggu, Seongnam 13120, Republic of Korea.
Email: [email protected]
Search for more papers by this authorCorresponding Author
Mehdi Hosseinzadeh
Pattern Recognition and Machine Learning Lab, Gachon University, Seongnam, Republic of Korea
Correspondence
Nima Jafari Navimipour, Department of Computer Engineering, Kadir Has University, Istanbul, Turkey.
Email: [email protected], [email protected]
Mehdi Hosseinzadeh, Pattern Recognition and Machine Learning Lab, Gachon University, 1342 Seongnamdaero, Sujeonggu, Seongnam 13120, Republic of Korea.
Email: [email protected]
Search for more papers by this authorMohammad Hossein Moattar
Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
Search for more papers by this authorAso Darwesh
Information Technology Department, University of Human Development, Sulaymaniyah, Iraq
Search for more papers by this authorAbstract
Over the last decade, the landscape of cloud computing has been significantly changed. It has been known as a paradigm in which a shared pool of computing resources is accessible for users. The rapid growth of the healthcare environment provides better medical services to reduce costs and increase competition among healthcare providers. Despite its crucial role in the cloud, no thorough study exists in this domain. This article presents a systematic study for healthcare services in the cloud environment. A well-organized overview of all the databases has been explored. By clustering the research goals of the found papers, we have derived four main research groups. We have further evaluated the papers concerning the background of the paper, QoS parameters, application area, or methods used for applying and formulating the main ideas presented in the works. This survey emphasizes the challenges, needs, benefits of using cloud computing in healthcare systems and provides a comprehensive and detailed study on cloud healthcare services, strengths, and weaknesses of the existing methods. Highlighting cloud health services can be the major focus of research for developing the urban healthcare system.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
REFERENCES
- 1Mesbahi MR, Rahmani AM, Hosseinzadeh M. Highly reliable architecture using the 80/20 rule in cloud computing datacenters. Futur Gener Comput Syst. 2017; 77: 77-86.
- 2Azhir E, Navimipour NJ, Hosseinzadeh M, Sharifi A, Darwesh A. Query optimization mechanisms in the cloud environments: a systematic study. Int J Commun Syst. 2019; 32(8):e3940.
- 3Keshavarzi A, Haghighat AT, Bohlouli M. Online QoS prediction in the cloud environments using hybrid time-series data mining approach. Iran J Sci Technol Trans Electr Eng. 2020; 45: 1-18.
- 4Sharma G, Kalra S. A lightweight user authentication scheme for cloud-IoT based healthcare services. Iran J Sci Technol Trans Electr Eng. 2019; 43(1): 619-636.
- 5Gao F, Sunyaev A. Context matters: a review of the determinant factors in the decision to adopt cloud computing in healthcare. Int J Inf Manag. 2019; 48: 120-138.
- 6Praveena A, Bharathi B. An approach to remove duplication records in healthcare dataset based on Mimic deep neural network (MDNN) and chaotic whale optimization (CWO). Concurr Eng. 2021; 29(1): 58-67.
- 7de Macedo DDJ, de Araújo GM, Dutra ML, Dutra ST, Lezana ÁGR. Toward an efficient healthcare cloud IoT architecture by using a game theory approach. Concurr Eng. 2019; 27(3): 189-200.
- 8Dang LM, Piran MJ, Han D, Min K, Moon H. A survey on Internet of Things and cloud computing for healthcare. Electronics. 2019; 8(7): 768.
- 9Rahimi M, Jafari Navimipour N, Hosseinzadeh M, Moattar MH, Darwesh A. Toward the efficient service selection approaches in cloud computing. Kybernetes. 2021; ahead-of-print.
- 10Esmailiyan M, Amerizadeh A, Vahdat S, Ghodsi M, Doewes RI, Sundram Y. Effect of different types of aerobic exercise on individuals with and without hypertension: an updated systematic review. Curr Probl Cardiol. 2021;101034.
- 11Vahdat S, Shahidi S. D-dimer levels in chronic kidney illness: a comprehensive and systematic literature review. Proc Nat Acad Sci Ind Sect B Biol Sci. 2020; 90(5): 911-928.
10.1007/s40011-020-01172-4 Google Scholar
- 12Mohammadi M, Rashid TA, Karim SHT, et al. A comprehensive survey and taxonomy of the SVM-based intrusion detection systems. J Netw Comput Appl. 2021; 178:102983.
- 13Vahdat S. The role of IT-based technologies on the management of human resources in the COVID-19 era. Kybernetes. 2020; ahead-of-print.
- 14Pourghebleh B, Hayyolalam V, Anvigh AA. Service discovery in the Internet of Things: review of current trends and research challenges. Wirel Netw. 2020; 26(7): 5371-5391.
- 15Vahdat S. Vitamin D and kidney diseases: a narrative review. Int J Prev Med. 2020; 11(1): 195.
- 16Masrom M, Rahimli A. A review of cloud computing technology solution for healthcare system. Res J Appl Sci Eng Technol. 2014; 8(20): 2150-2153.
10.19026/rjaset.8.1212 Google Scholar
- 17Kumar PJ, Chaithra MA. A survey on cloud computing based health care for diabetes: analysis and diagnosis. IOSR J Comput Eng. 2015; 17(4): 109-117.
- 18Griebel L, Prokosch HU, Köpcke F, et al. A scoping review of cloud computing in healthcare. BMC Med Inform Decis Mak. 2015; 15(1): 1-16.
- 19Ali O, Shrestha A, Soar J, Wamba SF. Cloud computing-enabled healthcare opportunities, issues, and applications: a systematic review. Int J Inf Manag. 2018; 43: 146-158.
- 20Zhang S, Xu X, Peng J, Huang K, Li Z. Physical layer security in massive Internet of Things: delay and security analysis. IET Commun. 2018; 13(1): 93-98.
- 21Wang X, Jin Z. An overview of mobile cloud computing for pervasive healthcare. IEEE Access. 2019; 7: 66774-66791.
- 22Al-Issa Y, Ottom MA, Tamrawi A. eHealth cloud security challenges: a survey. J Healthcare Eng. 2019; 2019: 1-15.
- 23Bhatia T, Verma AK, Sharma G. Towards a secure incremental proxy re-encryption for e-healthcare data sharing in mobile cloud computing. Concurr Comput Pract Exper. 2020; 32(5):e5520.
- 24Kavitha K, Sharma S. Performance analysis of ACO-based improved virtual machine allocation in cloud for IoT-enabled healthcare. Concurr Comput Pract Exper. 2020; 32(21):e5613.
- 25Azad P, Navimipour NJ, Hosseinzadeh M. A fuzzy-based method for task scheduling in the cloud environments using inverted ant colony optimisation algorithm. Int J Bio-Inspired Comput. 2019; 14(2): 125-137.
- 26Ratnam KA, Dominic PDD. Cloud services-enhancing the Malaysian healthcare sector. Paper presented at: Proceedings of the 2012 International Conference on Computer & Information Science (ICCIS); 2012; IEEE; Kuala Lumpur, Malaysia.
- 27Alzahrani BA, Irshad A, Albeshri A, Alsubhi K. A provably secure and lightweight patient-healthcare authentication protocol in wireless body area networks. Wirel Pers Commun. 2021; 117(1): 47-69.
- 28Sharaf S, Shilbayeh NF. A secure G-cloud-based framework for government healthcare services. IEEE Access. 2019; 7: 37876-37882.
- 29Jaiswal, K, Sobhanayak S, Turuk AK, Bibhudatta SL, Mohanta BK, Jena D. An IoT-cloud based smart healthcare monitoring system using container based virtual environment in edge device. Proceedings of the 2018 International Conference on Emerging Trends and Innovations in Engineering and Technological Research (ICETIETR); 2018; IEEE; Ernakulam, India.
- 30Padmaja K, Seshadri R. A real-time secure medical device authentication for personal E-healthcare services on cloud computing. Int J Syst Assur Eng Manag. 2021; 1-11.
- 31Milani BA, Navimipour NJ. A comprehensive review of the data replication techniques in the cloud environments: major trends and future directions. J Netw Comput Appl. 2016; 64: 229-238.
- 32Lee JY, Lee JW, Kim SD. A quality model for evaluating software-as-a-service in cloud computing. Proceedings of the 2009 Seventh ACIS International Conference on Software Engineering Research, Management and Applications; 2009; IEEE; Haikou, China.
- 33Biswas S, Akhter T, Kaiser MS, Mamun SA. Cloud based healthcare application architecture and electronic medical record mining: an integrated approach to improve healthcare system. Proceedings of the 2014 17th International Conference on Computer and Information Technology (ICCIT); 2014; IEEE; Dhaka, Bangladesh.
- 34Pourghebleh B, Jafari Navimipour N. Towards efficient data collection mechanisms in the vehicular ad hoc networks. Int J Commun Syst. 2019; 32(5):e3893.
- 35Aznoli F, Navimipour NJ. Cloud services recommendation: reviewing the recent advances and suggesting the future research directions. J Netw Comput Appl. 2017; 77: 73-86.
- 36Hayyolalam V, Pourghebleh B, Pourhaji Kazem AA. Trust management of services (TMoS): investigating the current mechanisms. Trans Emerg Telecommun Technol. 2020; 31(10):e4063.
- 37Mohta A, Sahu RK, Awasthi LK. Robust data security for cloud while using third party auditor. Int J Adv Res Comput Sci Softw Eng. 2012; 2(2): 201–207.
- 38Mubarakali A, Ashwin M, Mavaluru D, Kumar AD. Design an attribute based health record protection algorithm for healthcare services in cloud environment. Multimed Tools Appl. 2020; 79(5): 3943-3956.
- 39Kashani MH, Madanipour M, Nikravan M, Asghari P, Mahdipour E. A systematic review of IoT in healthcare: applications, techniques, and trends. J Netw Comput Appl. 2021; 192:103164.
- 40Kartsakli E, Antonopoulos A, Alonso L, Verikoukis C. A cloud-assisted random linear network coding medium access control protocol for healthcare applications. Sensors. 2014; 14(3): 4806-4830.
- 41Yazdi FR, Hosseinzadeh M, Jabbehdari S. A priority-based MAC protocol for energy consumption and delay guaranteed in wireless body area networks. Wirel Pers Commun. 2019; 108(3): 1677-1696.
- 42Akhbarifar S, Javadi HHS, Rahmani AM, Hosseinzadeh M. A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment. Pers Ubiquit Comput. 2020; 1-17.
- 43Zhang M, Chen Y, Susilo W. PPO-CPQ: a privacy-preserving optimization of clinical pathway query for e-healthcare systems. IEEE Internet Things J. 2020; 7(10): 10660-10672.
- 44Xu B, Xu L, Cai H, Jiang L, Luo Y, Gu Y. The design of an m-health monitoring system based on a cloud computing platform. Enterprise Inf Syst. 2017; 11(1): 17-36.
- 45Hosseinzadeh M, Koohpayehzadeh J, Ghafour MY, et al. An elderly health monitoring system based on biological and behavioral indicators in Internet of Things. J Ambient Intell Humaniz Comput. 2020; 1-11.
- 46Lv Z, Qiao L. Analysis of healthcare big data. Futur Gener Comput Syst. 2020; 109: 103-110.
- 47Marques G, Pitarma R. An indoor monitoring system for ambient assisted living based on Internet of Things architecture. Int J Environ Res Public Health. 2016; 13(11): 1152.
- 48Rashed A, Ibrahim A, Adel A, Mourad B, Hatem A, Magdy M, Elgaml N, Khattab A. Integrated IoT medical platform for remote healthcare and assisted living. Proceedings of the 2017 Japan-Africa Conference on Electronics, Communications and Computers (JAC-ECC); 2017; IEEE; Alexandria, Egypt.
- 49De Venuto D, Annese VF, Sangiovanni-Vincentelli AL. The ultimate IoT application: a cyber-physical system for ambient assisted living. Proceedings of the 2016 IEEE International Symposium on Circuits and Systems (ISCAS); 2016; IEEE; Montreal, QC, Canada.
- 50Konstantinidis EI, Antoniou PE, Bamparopoulos G, Bamidis PD. A lightweight framework for transparent cross platform communication of controller data in ambient assisted living environments. Inform Sci. 2015; 300: 124-139.
- 51Zgheib R, De Nicola A, Villani ML, Conchon E, Bastide R. A flexible architecture for cognitive sensing of activities in ambient assisted living. Proceedings of the 2017 IEEE 26th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE); 2017; IEEE; Poznan, Poland.
- 52Corno F, De Russis L, Roffarello AM. A healthcare support system for assisted living facilities: an iot solution. Proceedings of the 2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC); 2016; IEEE; Atlanta, GA, USA.
- 53Manonmani M, Balakrishnan S. A review of semantic annotation models for analysis of healthcare data based on data mining techniques. Emerging Res Data Eng Syst Comput Commun. 2020; 1054: 231-238.
10.1007/978-981-15-0135-7_22 Google Scholar
- 54Guk K, Han G, Lim J, et al. Evolution of wearable devices with real-time disease monitoring for personalized healthcare. Nano. 2019; 9(6): 813.
- 55Lv Z, Chen D, Feng H, Zhu H, Lv H. Digital twins in unmanned aerial vehicles for rapid medical resource delivery in epidemics. IEEE Trans Intell Transp Syst. 2021; 1-9.
- 56Mehbodniya A, Neware R, Vyas S, Kumar MR, Ngulube P, Ray S. Blockchain and IPFS integrated framework in bilevel fog-cloud network for security and privacy of IoMT devices. Comput Math Methods Med. 2021; 2021: 1-9.
- 57Pourghebleh B, Hayyolalam V. A comprehensive and systematic review of the load balancing mechanisms in the Internet of Things. Clust Comput. 2019; 23: 1-21.
- 58McKenzie LM, Witter RZ, Newman LS, Adgate JL. Human health risk assessment of air emissions from development of unconventional natural gas resources. Sci Total Environ. 2012; 424: 79-87.
- 59Abbas A, Ali M, Shahid Khan MU, Khan SU. Personalized healthcare cloud services for disease risk assessment and wellness management using social media. Pervas Mob Comput. 2016; 28: 81-99.
- 60Prieto-Gonzalez L, Tamm G, Stantchev V. Towards a software engineering approach for cloud and IoT services in healthcare. Proceedings of the International Conference on Computational Science and its Applications; 2016; Springer; Beijing, China.
- 61Ramana AV, Sasidhar K. A cloud based framework for healthcare system and applying clustering methods for region wise analysis; 2018.
- 62Liu Y, Zhang L, Yang Y, et al. A novel cloud-based framework for the elderly healthcare services using digital twin. IEEE Access. 2019; 7: 49088-49101.
- 63Farid F, Elkhodr M, Sabrina F, Ahamed F, Gide E. A smart biometric identity management framework for personalised IoT and cloud computing-based healthcare services. Sensors. 2021; 21(2): 552.
- 64Schobel J, Pryss R, Schickler M, Reichert M. Towards flexible mobile data collection in healthcare. Proceedings of the 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS); 2016; IEEE; Belfast and Dublin, Ireland.
- 65Hossain MS, Muhammad G. Cloud-assisted industrial Internet of Things (IIOT)–enabled framework for health monitoring. Comput Netw. 2016; 101: 192-202.
- 66Yang Z, Zhou Q, Lei L, Zheng K, Xiang W. An IoT-cloud based wearable ECG monitoring system for smart healthcare. J Med Syst. 2016; 40(12): 1-11.
- 67Jaiswal K, Sobhanayak S, Mohanta BK, Jena D. IoT-cloud based framework for patient's data collection in smart healthcare system using raspberry-pi. Proceedings of the 2017 International Conference on Electrical and Computing Technologies and Applications (ICECTA); 2017; Ras Al Khaimah, United Arab Emirates
- 68Xie R, Khalil I, Badsha S, Atiquzzaman M. Fast and peer-to-peer vital signal learning system for cloud-based healthcare. Futur Gener Comput Syst. 2018; 88: 220-233.
- 69Srinivas J, Das AK, Kumar N, Rodrigues JJPC. Cloud centric authentication for wearable healthcare monitoring system. IEEE Trans Depend Secure Comput. 2018; 17(5): 942-956.
- 70Quwaider M, Jararweh Y. An efficient big data collection in body area networks. Proceedings of the 2014 5th International Conference on Information and Communication Systems (ICICS); 2014; IEEE; Irbid, Jordan.
- 71Chatterjee N, Shi J, García-Closas M. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat Rev Genet. 2016; 17(7): 392-406.
- 72Nasiri M, Minaei B, Kiani A. Dynamic recommendation: disease prediction and prevention using recommender system. Int J Basic Sci Med. 2016; 1(1): 13-17.
10.15171/ijbsm.2016.04 Google Scholar
- 73Abdelaziz A, Elhoseny M, Salama AS, Riad AM. A machine learning model for improving healthcare services on cloud computing environment. Measurement. 2018; 119: 117-128.
- 74Zhang C, Zhu L, Xu C, Lu R. PPDP: an efficient and privacy-preserving disease prediction scheme in cloud-based e-healthcare system. Futur Gener Comput Syst. 2018; 79: 16-25.
- 75Kumar PM, Lokesh S, Varatharajan R, Chandra Babu G, Parthasarathy P. Cloud and IoT based disease prediction and diagnosis system for healthcare using fuzzy neural classifier. Futur Gener Comput Syst. 2018; 86: 527-534.
- 76Karaca Y, Moonis M, Zhang YD, Gezgez C. Mobile cloud computing based stroke healthcare system. Int J Inf Manag. 2019; 45: 250-261.
- 77Verma P, Sood SK. Cloud-centric IoT based disease diagnosis healthcare framework. J Parallel Distrib Comput. 2018; 116: 27-38.
- 78Das A, Rad P, Choo KKR, Nouhi B, Lish J, Martel J. Distributed machine learning cloud teleophthalmology IoT for predicting AMD disease progression. Futur Gener Comput Syst. 2019; 93: 486-498.
- 79Fatima A, Colomo-Palacios R. Security aspects in healthcare information systems: a systematic mapping. Proc Comput Sci. 2018; 138: 12-19.
10.1016/j.procs.2018.10.003 Google Scholar
- 80Deshmukh P. Design of cloud security in the EHR for Indian healthcare services. J King Saud Univ Comput Inf Sci. 2017; 29(3): 281-287.
- 81Aledhari M. A new cryptography algorithm to protect cloud-based healthcare services. Proceedings of the 2017 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE); 2017; IEEE; Philadelphia, PA, USA.
- 82Daoud WB, Meddeb-Makhlouf A, Zarai F. A trust-based access control scheme for e-health cloud. Proceedings of the 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA); 2018; IEEE; Aqaba, Jordan.
- 83Dhillon PK, Kalra S. A secure multi-factor ECC based authentication scheme for cloud-IoT based healthcare services. J Ambient Intell Smart Environ. 2019; 11(2): 149-164.
- 84Misra SC, Kumar A, Munnangi AK. Cloud-based healthcare management: identifying the privacy concerns and their moderating effect on the cloud-based health-care services. Secur Priv. 2019; 2(3):e63.
- 85Tang W, Zhang K, Zhang D, Ren J, Zhang Y, Shen X. Fog-enabled smart health: toward cooperative and secure healthcare service provision. IEEE Commun Mag. 2019; 57(5): 42-48.
- 86Mubarakali A. Healthcare services monitoring in cloud using secure and robust healthcare-based BLOCKCHAIN (SRHB) approach. Mob Netw Appl. 2020; 25(4): 1330-1337.
