Influential Usage of Big Data and Artificial Intelligence in Healthcare

Author:

Yang Yan Cheng12ORCID,Islam Saad Ul3,Noor Asra3,Khan Sadia3,Afsar Waseem3,Nazir Shah3ORCID

Affiliation:

1. Foreign Language Department, Luoyang Institute of Science and Technology, Luoyang, Henan, China

2. Foreign Language Department/Language and Cognition Center, Hunan University, Changsha, Hunan, China

3. Department of Computer Science, University of Swabi, Swabi, Pakistan

Abstract

Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of people’s lives around the globe. Especially, ICT has led to a very needy and tremendous improvement in the health sector which is commonly known as electronic health (eHealth) and medical health (mHealth). Deep machine learning and AI approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases. For example, cardiovascular imaging has now accurate imaging combined with big data from the eHealth record and pathology to better characterize the disease and personalized therapy. In clinical work and imaging, cancer care is getting improved by knowing the tumor biology and helping in the implementation of precision medicine. The Markov model is used to extract new approaches for leveraging cancer. In this paper, we have reviewed existing research relevant to eHealth and mHealth where various models are discussed which uses big data for the diagnosis and healthcare system. This paper summarizes the recent promising applications of AI and big data in medical health and electronic health, which have potentially added value to diagnosis and patient care.

Funder

Provincial Social Science Achievements Review Committee

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modelling and Simulation,General Medicine

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