Intelligent Information Systems in Healthcare Sector: Review Study

被引:0
作者
Akila, Ayman [1 ]
Elhoseny, Mohamed [2 ]
Nour, Mohamed Abdalla [2 ]
机构
[1] Univ Sharjah, Dept Elect & Elect Engn, Sharjah, U Arab Emirates
[2] Univ Sharjah, Dept Informat Syst, Sharjah, U Arab Emirates
来源
ARTIFICIAL INTELLIGENCE FOR INTERNET OF THINGS (IOT) AND HEALTH SYSTEMS OPERABILITY, IOTHIC 2023 | 2024年 / 8卷
关键词
Intelligent Information Systems; healthcare; electronic health records; machine learning; natural language processing; computer vision; Internet of Things; telemedicine; clinical decision support; ethical considerations; IDENTIFY;
D O I
10.1007/978-3-031-52787-6_11
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This research review paper provides a comprehensive analysis of the recent advancements and applications of Intelligent Information Systems (IIS) in the healthcare sector. The study highlights the transformative potential of IIS in enhancing patient care, optimizing clinical decision-making, and improving operational efficiency within healthcare organizations. The paper examines key aspects of IIS, such as electronic health records, machine learning algorithms, natural language processing, and computer vision techniques, while also exploring their integration with Internet of Things (IoT) and telemedicine platforms. Moreover, this paper proposes a framework that utilizes IIS in healthcare sector. Furthermore, the review discusses the challenges and future research directions associated with the implementation of IIS in healthcare settings. Overall, this paper aims to provide a holistic understanding of the role of IIS in revolutionizing the healthcare industry and shaping its future.
引用
收藏
页码:127 / 144
页数:18
相关论文
共 35 条
  • [1] Privacy Analysis of Smart City Healthcare Services
    Alghanim, Amjad A.
    Rahman, Sk Md Mizanur
    Hossain, M. Anwar
    [J]. 2017 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM), 2017, : 394 - 398
  • [2] A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities
    Ali, Omar
    Abdelbaki, Wiem
    Shrestha, Anup
    Elbasi, Ersin
    Alryalat, Mohammad Abdallah Ali
    Dwivedi, Yogesh K.
    [J]. JOURNAL OF INNOVATION & KNOWLEDGE, 2023, 8 (01):
  • [3] Aljabr A.A., 2022, Meas. Sens, V24
  • [4] Ara Affreen, 2017, 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), P3179, DOI 10.1109/ICECDS.2017.8390043
  • [5] An intelligent IoT with cloud centric medical decision support system for chronic kidney disease prediction
    Arulanthu, Pramila
    Perumal, Eswaran
    [J]. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2020, 30 (03) : 815 - 827
  • [6] Aruna M., 2022, Medical healthcare system with hybrid block based predictive models for quality preserving in medical images using machine learning techniques
  • [7] Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients
    Bates, David W.
    Saria, Suchi
    Ohno-Machado, Lucila
    Shah, Anand
    Escobar, Gabriel
    [J]. HEALTH AFFAIRS, 2014, 33 (07) : 1123 - 1131
  • [8] Berner ES, 2016, HEALTH INFORM SER, P1, DOI 10.1007/978-3-319-31913-1_1
  • [9] Big Data Modelling for Predicting Side-Effects of Anticancer Drugs: A Comprehensive Approach
    Bolla, Sai Jyothi
    Jyothi, S.
    [J]. INTELLIGENT SYSTEMS AND APPLICATIONS, VOL 1, 2020, 1037 : 446 - 456
  • [10] Conejar R.J., 2016, Int. J. Smart Home, V10, P283