scholarly journals Influential Usage of Big Data and Artificial Intelligence in Healthcare

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yan Cheng Yang ◽  
Saad Ul Islam ◽  
Asra Noor ◽  
Sadia Khan ◽  
Waseem Afsar ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Tumor Biology ◽  
Health Sector ◽  
Clinical Work ◽  
Information And Communications Technology ◽  
Added Value ◽  
Medical Health ◽  
Electronic Health

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.

scholarly journals Big data - a review in health sciences

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ayça Kurnaz Türkben ◽  
Emre Türkben ◽  
Dilek Karahoca ◽  
Adem Karahoca
Keyword(s):  
Big Data ◽  
Health Sector ◽  
Health Sciences ◽  
Health Science ◽  
Mobile Technologies ◽  
Review Of Literature ◽  
Public And Private ◽  
Review Study ◽  
The Cost

Technologies are changing very fast and data has an impact on the change of technology and development of world. Data are obtained by social media, the Internet and mobile technologies. For years, academics, researchers and companies utilize some sources and information to analyze them for their studies and jobs. Increasing usage of mobile devices, social networks, electronic records of customers in public and private sectors have led to increase in data. Obtained massive amount of data is called big data. There are a lot of description of big data in the literature, but simply it can be said that; big data is the data which have a massive size and can be obtained from every environment. One of these environment is health environment and it has grown fastly through that huge amount of data exist in this sector like patients’ electronic health record. Health sector has a high cost and decision will be taken as soon as possible and correctly in this sector in which timing is critically important. In this manner, the usage of big data in health is important to increase the quality of service, innovative health operations and decrease the cost. In this study, a brief review of literature has done for the use of big data in health sciences for last five years. Big data’s content, methods, advantages and difficulties are discussed in this review study. Keywords: Health science, Big data, Medicine, data mining

scholarly journals Applications of Artificial Intelligence (AI) in healthcare: A review

2021 ◽  
Author(s):  
Mohammed Yousef Shaheen
Keyword(s):  
Artificial Intelligence ◽  
Clinical Trials ◽  
Drug Discovery ◽  
Target Identification ◽  
Health Sector ◽  
Monitoring Methods ◽  
Pharmaceutical Firms ◽  
Genetic Codes ◽  
Applications Of Ai

Artificial intelligence is revolutionizing — and strengthening — modern healthcare through technologies that can predict, grasp, learn, and act, whether it's employed to identify new relationships between genetic codes or to control surgery-assisting robots. It can detect minor patterns that humans would completely overlook. This study explores and discusses the various modern applications of AI in the health sector. Particularly, the study focuses on three most emerging areas of AI-powered healthcare: AI-led drug discovery, clinical trials, and patient care. The findings suggest that pharmaceutical firms have benefited from AI in healthcare by speeding up their drug discovery process and automating target identification. Artificial Intelligence (AI) can help also to eliminate time-consuming data monitoring methods. The findings also indicate that AI-assisted clinical trials are capable of handling massive volumes of data and producing highly accurate results. Medical AI companies develop systems that assist patients at every level. Patients' medical data is also analyzed by clinical intelligence, which provides insights to assist them improve their quality of life.

scholarly journals Big data in the healthcare system: a synergy with artificial intelligence and blockchain technology

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Reyes-González Juan Pablo ◽  
Díaz-Peregrino Roberto ◽  
Soto-Ulloa Victor ◽  
Galvan-Remigio Isabel ◽  
Castillo Paul ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Healthcare System ◽  
Medical Doctors ◽  
Blockchain Technology ◽  
System A ◽  
Healthcare Professions ◽  
State Of Art ◽  
Digital Anatomy

Abstract In the last decades big data has facilitating and improving our daily duties in the medical research and clinical fields; the strategy to get to this point is understanding how to organize and analyze the data in order to accomplish the final goal that is improving healthcare system, in terms of cost and benefits, quality of life and outcome patient. The main objective of this review is to illustrate the state-of-art of big data in healthcare, its features and architecture. We also would like to demonstrate the different application and principal mechanisms of big data in the latest technologies known as blockchain and artificial intelligence, recognizing their benefits and limitations. Perhaps, medical education and digital anatomy are unexplored fields that might be profitable to investigate as we are proposing. The healthcare system can be revolutionized using these different technologies. Thus, we are explaining the basis of these systems focused to the medical arena in order to encourage medical doctors, nurses, biotechnologies and other healthcare professions to be involved and create a more efficient and efficacy system.

scholarly journals Big Data and the Threat to Moral Responsibility in Healthcare

2021 ◽  
pp. 11-25
Author(s):  
Daniel W. Tigard
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Moral Responsibility ◽  
Intelligent Systems ◽  
Healthcare Systems ◽  
Ethical Challenges ◽  
Trade Offs ◽  
The Social ◽  
Healthcare Technologies

AbstractTechnological innovations in healthcare, perhaps now more than ever, are posing decisive opportunities for improvements in diagnostics, treatment, and overall quality of life. The use of artificial intelligence and big data processing, in particular, stands to revolutionize healthcare systems as we once knew them. But what effect do these technologies have on human agency and moral responsibility in healthcare? How can patients, practitioners, and the general public best respond to potential obscurities in responsibility? In this paper, I investigate the social and ethical challenges arising with newfound medical technologies, specifically the ways in which artificially intelligent systems may be threatening moral responsibility in the delivery of healthcare. I argue that if our ability to locate responsibility becomes threatened, we are left with a difficult choice of trade-offs. In short, it might seem that we should exercise extreme caution or even restraint in our use of state-of-the-art systems, but thereby lose out on such benefits as improved quality of care. Alternatively, we could embrace novel healthcare technologies but in doing so we might need to loosen our commitment to locating moral responsibility when patients come to harm; for even if harms are fewer – say, as a result of data-driven diagnostics – it may be unclear who or what is responsible when things go wrong. What is clear, at least, is that the shift toward artificial intelligence and big data calls for significant revisions in expectations on how, if at all, we might locate notions of responsibility in emerging models of healthcare.

scholarly journals Big Data Analytics & Artificial Intelligence in Healthcare

2021 ◽  
Author(s):  
PRANJAL KUMAR ◽  
Siddhartha Chauhan
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Health Sector ◽  
Big Data Analytics ◽  
Personal Data ◽  
Related Data ◽  
Large Scale Data ◽  
Ethical Policy ◽  
Health Related

Abstract Big data analysis and Artificial Intelligence have received significant attention recently in creating more opportunities in the health sector for aggregating or collecting large-scale data. Today, our genomes and microbiomes can be sequenced i.e., all information exchanged between physicians and patients in Electronic Health Records (EHR) can be collected and traced at least theoretically. Social media and mobile devices today obviously provide many health-related data regarding activity, diets, social contacts, and so on. However, it is increasingly difficult to use this information to answer health questions and, in particular, because the data comes from various domains and lives in different infrastructures and of course it also is very variable quality. The massive collection and aggregation of personal data come with a number of ethical policy, methodological, technological challenges. It should be acknowledged that large-scale clinical evidence remains to confirm the promise of Big Data and Artificial Intelligence (AI) in health care. This paper explores the complexities of big data & artificial intelligence in healthcare as well as the benefits and prospects.

Artificial Intelligence Applications for Event Management and Marketing

2021 ◽  
pp. 199-215
Author(s):  
Fatma Doğanay Ergen
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Competitive Advantage ◽  
New Products ◽  
Added Value ◽  
Future Trends ◽  
Event Management ◽  
Artificial Intelligence Technology ◽  
Telepresence Robots ◽  
Robotic Applications

The current use of artificial intelligence technology in the event industry, its effects on the industry, and future trends are discussed within the scope of this section. The use of artificial intelligence technology that provided by big data draws attention. In the event industry, it is known that robotic applications (telepresence robots, robotic concierge, robot bartenders, robot peacekeepers, robot servers, robot deliveries, and entertainment robots), digital assistants, and chatbots are used within the scope of artificial intelligence technology. It has been determined that artificial intelligence technology offers the stakeholders opportunities to gain competitive advantage, to obtain information that can be used in marketing efforts, to enable digitalization in manual processes, to improve customer interactions, to increase event participation with lower costs, and to create added value with new products and services. It is predicted that this progress will continue in the future and the use of artificial intelligence technology in the event industry will expand.

Personalized dynamic evaluation technology of online education quality management based on artificial intelligence big data

2021 ◽  
pp. 1-10
Author(s):  
Xujing Bai ◽  
Jiajun Li
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Quality Management ◽  
Online Education ◽  
Online Teaching ◽  
Functional Module ◽  
Education Quality ◽  
Model Framework ◽  
Dynamic Evaluation

Limited by the difficulty of management, the quality of online education is far worse than the quality of classroom teaching. In order to improve the effect of online education quality management, according to the actual needs of online teaching, this article builds personalized dynamic evaluation technology based on artificial intelligence big data technology and uses evaluation as the center of teaching. Each link in the teaching is for the generation and development of evaluation, and the teaching plan takes the learning objectives as the basis for the entire teaching process. Moreover, this research combines the needs analysis to build each functional module and build a model framework on this basis. In addition, in order to verify the performance of the model, this article conducts model analysis through practical teaching methods. The research results show that the model constructed in this paper has good performance.

scholarly journals Analysis Of The Variables Of Intention Of The Adoption And Acceptance Of Artificial Intelligence And Big Data Tools Among Leaders Of Organizations In Morocco: Attempt Of A Theoretical Study

2021 ◽  
Vol 17 (29) ◽  
pp. 106
Author(s):  
Moudni Yousra ◽  
Chafik Khalid
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Business Performance ◽  
New Technologies ◽  
Added Value ◽  
Research Model ◽  
Current State ◽  
Behavioral Variables ◽  
Industry Sectors ◽  
Do So

Artificial intelligence and big data are two emerging technologies that is now gaining ground among organizations. Their added value and their impact on business performance differ from one industry to another. Due to increased competitiveness, and in order to survive in the market, companies are led to adopt these new technologies that will enable them to be more performant and offer customers goods or services that meet their real needs since this approach is based on data collected from outside the company's environment. To do so, it is important to know and analyze beforehand the factors and variables that impact the adoption and acceptance process in order to manage them. This paper focuses on establishing a synthetic literature review to find out the current state of researches on the problems of AI and Big data adoption and acceptance, and it also argument the empirical sector’s choice. The findings of this study show that agricultural and chemical industry sectors are the two most promising sectors for AI in Morocco. As a result, a comparative analysis will be conducted after the development of the research model on these two fields in order to analyze the variables of adoption and acceptance of AI. Also, the most influential variables according to the literature were detected in this paper, which are grouped into four (4) types: technological, organizational, environmental, and behavioral variables.

scholarly journals Solutions for data management in the health sector

2020 ◽  
Vol 2 (1) ◽  
pp. 178-190
Author(s):  
Crina-Dana Ionescu ◽  
Emilia Ţiţan ◽  
Mihaela Mihai ◽  
Daniela-Ioana Manea ◽  
Andra Nechifor
Keyword(s):  
Data Management ◽  
Health Sector ◽  
Decision Makers ◽  
Added Value ◽  
The Political ◽  
Political Decision ◽  
X Ray ◽  
Medical Sector

Abstract The lack of data for many indicators and the existence of significant gaps in the availability and comparability of data is a problem of global interest, felt by all authorities and agencies specialized in data collection, analysis and use. Their objective is to provide data and indicators of good quality, which will help to correctly inform the political decision-makers and to solve the inequalities in the field of health. Thus, this paper aims to provide clear and coherent solutions to a number of problems identified in data management in general, and in data in the medical sector in particular. Also, the added value of this paper consists in a case study, which presents an x-ray of the current situation of data quality through the existing metadata for each of the analyzed sources. The research methodology used in the paper includes both a thorough analysis of the literature that identifies the main data problems and provides related solutions, as well as a comparative analysis on the quality of health data, using metadata from three sources and distinct levels of aggregation: National (Romania), European and Global.

scholarly journals Insurance Market of Ukraine in Conditions of Regulatory and Digital Transformation

2020 ◽  
Author(s):  
Olha Hladchuk ◽  
Volodymyr Odochuk
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Digital Transformation ◽  
Insurance Market ◽  
Institutional Characteristics ◽  
Market Participants ◽  
Mobile Access ◽  
Regulatory Changes ◽  
Quantitative Indicators

The Ukrainian insurance market shows an increase in quantitative indicators of activity, but the functional and institutional characteristics do not meet modern requirements. Now the insurance market of Ukraine is undergoing important regulatory changes, as a result of which the NBU is beginning to regulate the work of insurers, which gives hope for increasing the quality of activity of insurance market participants. Modern financial technologies have transformed the insurance market, they include big data, artificial intelligence, blockchain, mobile access, which gave impetus to the creation of new insurance products and created opportunities for facilitating clients' access to insurance services.

Sign in / Sign up

Export Citation Format

Share Document