Research Review on Predicting Cardio Vascular Diseases through Big Data

Introduction of Research Review on Predicting Cardio-Vascular Diseases through Big Data

In recent years the technology around the world has globe advanced up to a lot of extents. in many healthcare organizations, the record management and collection of patient's data has improved up to a lot of extents. Today the healthcare organization efficiently maintains the record of their patients so that it can be used for providing high-quality healthcare service. The patients’ historical data can be analyzed using different big data analytics. Big data analytics helps healthcare professionals to identify the disease and treat it accordingly.

The researchers in the research studies have discussed how big data can be used efficiently in the medical field for analysis of cardiovascular disease. The findings of the research studies indicate that data analytics should be used for the analysis of big data. The big data analytics which is used might have limitations and cannot analyze the data efficiently. However different big data analytics overcome those limitations and can help healthcare professionals in analyzing big data regarding cardiovascular diseases. According to the researchers, future research is required for performing further research to identify how big data analytics can be utilized more efficiently in big data analysis

Sources of Research Review on Predicting Cardio-Vascular Diseases through Big Data        

The research articles are searched using google scholar, IEEE explores and Sage journals. From the mentioned sources 5 research articles that are regarding the big data analytics are chosen.

Discussion of method of Research Review on Predicting Cardio-Vascular Diseases through Big Data

To perform the research study extensive amount of data needs to be gathered so that the research can provide answers to the research questions. The research methodology which most of the research studies follow includes a quantitative research approach or a qualitative research approach. The researchers follow different research designs which include descriptive, experimental and sometimes exploratory research design for providing information regarding the research problem. the data which is gathered by the researchers is primary or secondary. Most of the research studies gathered both primary and secondary data so that the research can analyze the research problem critically.

The primary data is gathered using the primary data collection methods which include interviews and survey methods. There are many studies in which the survey is conducted by the researchers and data is collected from the respondents. The qualitative studies usually utilized the survey approach for gathering the data. The sample is taken from the population and then data is collected from respondents.in qualitative studies interviews are conducted from the respondents. There are also such studies which combine qualitative and quantitative approaches so that research problem can be analyzed deeply and detailed information can be given. The research method chosen by the researchers has a significant impact on the findings of the research studies.

The research study conducted by Munaza Ramzan and Sanjeev Thakur (2016) has provided detail insights regarding cardiovascular disease and how cardiovascular disease can be predicted or analyzed using big data. In the research study, the researchers have provided detail information about the types of cardiovascular diseases. The researchers have identified the types of cardiovascular diseases on which the technique of big data analytics can be applied. For conducting the research the researchers have utilized the secondary data. An extensive literature review has been performed to gather information about the use of big data analytics in the medical field. In simple words, secondary research methodology is adopted by the researcher.

Source: (Thakur & Ramzan, 2016)

The researchers in the research study have discussed how big data can be used efficiently in the medical field for analysis of cardiovascular disease. The findings of the research studies indicate that Hadoop should be used for the analysis of big data. The big data analytics which is used have their limitations and cannot analyze the data efficiently. However, Hadoop overcomes those limitations and can help healthcare professionals in analyzing the big data regarding cardiovascular diseases. According to the researchers, future research is required for performing further research to identify how Hadoop can be utilized more efficiently in big data analysis (Thakur & Ramzan, 2016).

The research study conducted by Suma Swamy and Salma Banu N.k. (2016) have provided brief information about heart diseases and how heart diseases can be predicted using big data analytics. Big data analytic provide the opportunity to analyses the big data and give information in detail. The big data in the medical sector include the information of the patients over a specific time. Big data is analyzed to predict heart disease by looking at the medical history of the patient.

The researchers in the research study have conducted a literature survey from 2004 to 2016 to identify various big data analytics approaches. Not only different big data analytic approaches are discussed but also the accuracy of the big data analytics approach is also discussed in the research study. The findings of the research have shown different big data analytics and which techniques are the most accurate. Different approaches are compared in the research study. Although the study has provided information in detail it has its limitations. Future research can remove the limitations of the research study (N.K & Swamy, 2016).

Thomas M. Maddox, John S. Rumsfeld and Karen E. Joyant (2016) have provided significant of the big data analytics in cardiovascular care. According to the researchers, cardiovascular care can be improved significantly through big data analytics. Big data provides the medical history of the patients. If the big data of cardiovascular patients is analyzed using big data analytics accurately than cardiovascular diseases can be identified and treated on time. In this research, the researchers have gathered data through an extensive literature review. Various studies have been analyzed for providing a review regarding cardiovascular diseases. The research has utilized secondary research methodology.

Source: (S. Rumsfeld, et al., 2016).

The findings of the research study have shown that cardiovascular diseases can be identified efficiently through big data analytics. In the research study for improving cardiovascular care, the researchers have identified 8 areas where big data sources and analytics should be applied. According to the researchers if big data analytics are applied in these areas efficiently than cardiovascular care can be improved up to a lot of extents. The latest technologies can play an important role in the improvement of healthcare services. Not only the diseases can be identified on time but also their treatment can be done more effectively with the latest technological approaches (S. Rumsfeld, et al., 2016).

The study conducted by Lidong Wang and Cheryl Ann Alexander (2017) has provided detail information about the importance of big data analytics. The researchers have stated that big data analytics can be used for predicting medical conditions such as heart attacks. For conducting this research the extensive literature review is done. The researchers have selected the research studies which meet the criteria of the research study. It can be said that the study primarily based on the studies which have been selected by the researchers. The studies have discussed the usefulness and effectiveness of big data analytics in the medical field.

The findings of the study have shown that big data analytics can play an important role in the identification, prevention, and treatment of the diseases. The data analytics tools such as Hadoop can be utilized for big data analytics. The tools such as Hadoop are not only cost-effective but are also fast and reliable. The findings of the studies which are used for this study show that for predicting heart attack big data analytics should be utilized. This research study has provided the latest information about big data analytics and how they can be utilized (Alexander & Wang, 2017).

The research study conducted by Shih-Lin Wu, Prasan Kumar Sahoo, and Suvendu Kumar Mohapatra has discussed the analysis of big data. The researchers in the study have utilized primary and secondary data. The findings of the study show that big data analytics can predict the healthcare conditions of the patients. The technological advancements can revolutionize the healthcare sector. The latest technologies can change the way how patients are being treated. The latest technologies aim to provide maximum convenience to healthcare providers and patients. In short, technological advancement is bringing maximum benefit for the patients (Sahoo, et al., 2016).

Findings of Research Review on Predicting Cardio-Vascular Diseases through Big Data

The researches mentioned above have utilized the secondary research methodology instead of primary. By using the secondary research methodology the researchers have provided brief information regarding the research problem and answered the research questions appropriately. In the above research studies, the researchers have not utilized the techniques such as surveys, interviews or any other approach for gathering the data. The research studies mentioned above have utilized a literature review for the collection of data. In other words, an extensive literature survey has been done to conduct the study. As discussed earlier the research methodology which the researchers choose has a significant impact on the findings of the study.

The research study conducted by Munaza Ramzan and Sanjeev Thakur (2016) has provided detail insights regarding cardiovascular disease and how cardiovascular disease can be predicted or analyzed using big data. Although the researchers have successfully answered the researches questions by gathering data through extensive literature review it is recommended that primary research should also be done to understand how data analytics can help in predicting cardiovascular diseases. The collection of primary data can provide new information that the existing literature might not provide. The research has focused mainly on existing information. Furthermore, the research has mainly focused on one data analytic tool that is Hadoop. There are many other tools as well that can work efficiently. The researchers should include other tools in the study as well so that it can be understood which tool works the best (Thakur & Ramzan, 2016).

The research study conducted by Suma Swamy and Salma Banu N.k. (2016) have provided brief information about heart diseases and how heart diseases can be predicted using big data analytics. In this research study, the data is gathered using the literature review. An extensive literature survey is performed for conducting the study. It can be said that the whole study is based on the existing literature. The researchers have not gathered data from primary sources which means that new information has not included in the research study. There is also a major limitation of the research study. The study is conducted from the period of 2004 to 2016. It means that the techniques originated after 2016 or existed before 2004 are not included in the research study. It means that the information given by the study is not useful for a longer time (N.K & Swamy, 2016).

Thomas M. Maddox, John S. Rumsfeld and Karen E. Joyant (2016) have provided significant of the big data analytics in cardiovascular care. According to the researchers cardio, vascular care can be improved significantly through big data analytics. The researchers have gathered the information by reviewing different research studies and have not gathered the data using the primary research approaches. The lack of primary data collection means that the study realizes on the existing information and have not gathered new information. Also the research the researchers have identified 8 areas where data analytics can be applied for improvement of cardiovascular care. This limits the research to these 8 areas only (S. Rumsfeld, et al., 2016).

The study conducted by Lidong Wang and Cheryl Ann Alexander (2017) has provided detail information about the importance of big data analytics. According to the researchers the analytics software can be utilized for the prediction of heart diseases. The research has its limitations. The first key limitation of this research is that it is primarily based on the existing literature. It is important to include primary data in the study as well so that new information can be given to the general public. The primary data is a way of collecting new data (Alexander & Wang, 2017).

The research study conducted by Shih-Lin Wu, Prasan Kumar Sahoo, and Suvendu Kumar Mohapatra has discussed the analysis of big data. The analysis of big data helps healthcare professionals to analyze the health conditions of their patients. In this study, the researchers have collected a significant amount of data which enhances the credibility and reliability of the research. Although the research has provided brief information and contributed new information in the existing literature future research can be carried on for a further analysis of the use of big data analytics in the medical field and how different diseases can be identified (Sahoo, et al., 2016).

Limitations of Research Review on Predicting Cardio-Vascular Diseases through Big Data

The research methodology which is used for collecting the information has its advantages and disadvantages. If the researchers only rely on secondary data and not going to collect primary data than there are chances that the researchers will provide information that is based on the existing findings or information. The primary data collection helps the researchers to collect new information from the respondents. Through this not only the researchers can analyze the research problem more critically but also the credibility and reliability of the researches will enhance up to a lot of extents. Therefore it is recommended to utilize both secondary and primary data collection techniques.

Conclusion of Research Review on Predicting Cardio-Vascular Diseases through Big Data

It is concluded that the healthcare organization efficiently maintain the record of their patients so that it can be used for providing high-quality healthcare service. The patients’ historical data can be analyzed using different big data analytics. The big data analytics helps healthcare professionals to identify the disease and treat it accordingly.  Big data analytic provide the opportunity to analyses the big data and give information in detail. The big data in the medical sector include the information of the patients over a specific time. Big data is analyzed to predict heart disease by looking at the medical history of the patient.

The researches mentioned above have utilized the secondary research methodology instead of primary. By using the secondary research methodology the researchers have provided brief information regarding the research problem and answered the research questions appropriately. In the above research studies, the researchers have not utilized the techniques such as surveys, interviews or any other approach for gathering the data. The research studies mentioned above have utilized a literature review for the collection of data. In other words, an extensive literature survey has been done to conduct the study. As discussed earlier the research methodology which the researchers choose has a significant impact on the findings of the study. The research methodology which is used for collecting the information has its advantages and disadvantages. If the researchers only rely on secondary data and not going to collect primary data than there are chances that the researchers will provide information that is based on the existing findings or information.

 References of Research Review on Predicting Cardio-Vascular Diseases through Big Data

Alexander, C. A. & Wang, L., 2017. Big Data Analytics in Heart Attack Prediction. Journal of Nursing and Care, 6(2), pp. 1-9.

N.K, S. B. & Swamy, S., 2016. Prediction of Heart Disease at an early stage using Data Mining and Big Data Analytics: A Survey. pp. 256-261.

S. Rumsfeld, J., E. Joynt, K. & M. Maddox, T., 2016. Big data analytics to improve cardiovascular care: promise and challenges. NATURE REVIEWS, pp. 1-10.

Sahoo, P. K., Mohapatra, S. K. & Wu, S.-L., 2016. Analyzing Healthcare Big Data With Prediction for Future Health Condition. Volume 4, pp. 9786 - 9799.

Thakur, S. & Ramzan, M., 2016. A Systematic Review On Cardiovascular diseases using Big-Data by Hadoop.. pp. 351-355.