scholarly journals Big Data, Extracting Insights, Comprehension, and Analytics in Cardiology: An Overview

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hui Xiao ◽  
Sikandar Ali ◽  
Zhen Zhang ◽  
Muhammad Shahzad Sarfraz ◽  
Fang Zhang ◽  
...  

Healthcare system facilitates the treatment of patients with the support of wearable, smart, and handheld devices, as well as many other devices. These devices are producing a huge bulk of data that need to be moulded for extracting meaningful insights from them for the useful use of researchers and practitioners. Various approaches, methods, and tools are in use for doing so and to extract meaningful information in the field of healthcare. This information is being used as evidence to further analyze the data for the early care of patient and to devise treatment. Early care and treatment can facilitate healthcare and the treatment of the patient and can have immense potentiality of dropping the care cost and quality refining of care and can decrease waste and chances of error. To facilitate healthcare in general and cardiology in specific, the proposed study presents an overview of the available literature associated with big data, its insights, and analytics. The presented report will help practitioners and researchers to devise new solutions for early care in healthcare and in cardiology.

2017 ◽  
Author(s):  
Mohammed Shukur ◽  
Laith Fliah ◽  
Aram Abdulqadir
Keyword(s):  
Big Data ◽  

2021 ◽  
pp. 31-52
Author(s):  
Grazia Dicuonzo ◽  
Francesca Donofrio ◽  
Antonio Fusco ◽  
Vittorio Dell’Atti

This paper investigates the digitalization challenges facing the Italian healthcare system. The aim of the paper is to support healthcare organizations as they take advantage of the potential of big data and artificial intelligence (AI) to promote sustainable healthcare systems. Both the development of innovative processes in the management of health care activities and the introduction of healthcare forecasting systems are valuable resources for clinical and care activities and enable a more efficient use of inputs in essential-level care delivery. By examining an innovative project developed by the Regional Social Health Agency (ARSS) of Veneto, this study analyses the impact of big data and AI on the sustainability of a healthcare system. In order to answer the research question, we used a case study methodology. We conducted semi-structured interviews with key members of the organizational group involved in the case. The results show that the implementation of AI algorithms based on big data in healthcare both improves the interpretation and processing of data, and reduces the time frame necessary for clinical processes, having a positive effect on sustainability.


Author(s):  
Sunny Sharma ◽  
Manisha Malhotra

Web usage mining is the use of data mining techniques to analyze user behavior in order to better serve the needs of the user. This process of personalization uses a set of techniques and methods for discovering the linking structure of information on the web. The goal of web personalization is to improve the user experience by mining the meaningful information and presented the retrieved information in a way the user intends. The arrival of big data instigated novel issues to the personalization community. This chapter provides an overview of personalization, big data, and identifies challenges related to web personalization with respect to big data. It also presents some approaches and models to fill the gap between big data and web personalization. Further, this research brings additional opportunities to web personalization from the perspective of big data.


Author(s):  
Shannon Wai Yi Yee ◽  
Carolina Gutierrez ◽  
Caroline Narae Park ◽  
Danny Lee ◽  
Scott Lee

In the last three decades, big data has been applied to diverse fields, such as the government, international development, and education. It is only now that the US healthcare system has begun to explore its under-utilized data. Big data is not only referencing the quantity, but also the complexity, diversity, and relativity of the information. This information may be analyzed to reveal patterns, trends, and associations that may be applicable to the healthcare field. This information can be gathered through sources, such as EHRs, IRIS registry, and MIPS. Recognizing patterns would aid in predicting preventative measures for an increased holistic and personalized patient care. Although big data proves to have endless beneficial applications, it can bring into question the ownership of this information. Additionally, big data poses a risk for security breaches, and thus, precautionary measures will also be discussed. Ultimately, the emergence of big data creates an exhilarating frontier for healthcare with its unlimited possibilities.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ginevra Gravili ◽  
Francesco Manta ◽  
Concetta Lucia Cristofaro ◽  
Rocco Reina ◽  
Pierluigi Toma

PurposeThe aim of this paper is to analyze and measure the effects of intellectual capital (IC), i.e. human capital (HC), relational capital (RC) and structural capital (SC), on healthcare industry organizational performance and understanding the role of data analytics and big data (BD) in healthcare value creation (Wang et al., 2018). Through the assessment of determined variables specific for each component of IC, the paper identifies the guidelines and suggests propositions for a more efficient response in terms of services provided to citizens and, specifically, patients, as well as predicting effective strategies to improve the care management efficiency in terms of cost reduction.Design/methodology/approachThe study has a twofold approach: in the first part, the authors operated a systematic review of the academic literature aiming to enquire the relationship between IC, big data analytics (BDA) and healthcare system, which were also the descriptors employed. In the second part, the authors built an econometric model analyzed through panel data analysis, studying the relationship between IC, namely human, relational and structural capital indicators, and the performance of healthcare system in terms of performance. The study has been conducted on a sample of 28 European countries, notwithstanding the belonging to specific international or supranational bodies, between 2011 and 2016.FindingsThe paper proposes a data-driven model that presents new approach to IC assessment, extendable to other economic sectors beyond healthcare. It shows the existence of a positive impact (turning into a mathematical inverse relationship) of the human, relational and structural capital on the performance indicator, while the physical assets (i.e. the available beds in hospitals on total population) positively mediates the relationship, turning into a negative impact of non-IC related inputs on healthcare performance. The result is relevant in terms of managerial implications, enhancing the opportunity to highlight the crucial role of IC in the healthcare sector.Research limitations/implicationsThe relationship between IC indicators and performance could be employed in other sectors, disseminating new approaches in academic research. Through the establishment of a relationship between IC factors and performance, the authors implemented an approach in which healthcare organizations are active participants in their economic and social value creation. This challenges the views of knowledge sharing deeply held inside organizations by creating “new value” developed through a more collaborative and permeated approach in terms of knowledge spillovers. A limitation is given by a fragmented policymaking process which carries out different results in each country.Practical implicationsThe analysis provides interesting implications on multiple perspectives. The novelty of the study provides interesting implications for managers, practitioners and governmental bodies. A more efficient healthcare system could provide better results in terms of cost minimization and reduction of hospitalization period. Moreover, dissemination of new scientific knowledge and drivers of specialization enhances best practices sharing in the healthcare sector. On the other hand, an improvement in preventive medicine practices could help in reducing the overload of demand for curative treatments, on the perspective of sharply decreasing the avoidable deaths rate and improving societal standards.Originality/valueThe authors provide a new holistic framework on the relationship between IC, BDA and organizational performance in healthcare organizations through a systematic review approach and an empirical panel analysis at a multinational level, which is quite a novelty regarding the healthcare. There is little research focussed on healthcare industries' organizational performance, and, specifically, most of the research on IC in healthcare delivered results in terms of theoretical contribution and qualitative analyzes. The authors even contributed to analyze the healthcare industry in the light of the possible existence of synergies and networks among countries.


2020 ◽  
Vol 28 (2) ◽  
pp. 142-147 ◽  
Author(s):  
Nian-Shing Chen ◽  
Chengjiu Yin ◽  
Pedro Isaias ◽  
Joseph Psotka

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