Relevant bibliographies by topics / Big data in healthcare

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Big data in healthcare'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 July 2025

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Journal articles on the topic "Big data in healthcare"

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Patil, Pratiksha. "Big Data in Healthcare." International Journal of Science and Research (IJSR) 11, no. 1 (2022): 1229–31. http://dx.doi.org/10.21275/sr22124093041.

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Viceconti, Marco, Peter Hunter, and Rod Hose. "Big Data, Big Knowledge: Big Data for Personalized Healthcare." IEEE Journal of Biomedical and Health Informatics 19, no. 4 (2015): 1209–15. http://dx.doi.org/10.1109/jbhi.2015.2406883.

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Sarkar, Bikash Kanti. "Big Data and Healthcare Data." International Journal of Knowledge-Based Organizations 7, no. 4 (2017): 50–77. http://dx.doi.org/10.4018/ijkbo.2017100104.

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Big data and its analytics yield a lot of opportunities to make great progresses in many fields, ranging from economic and business activities to public administration, from national security to scientific researches and so on. However, the most noticeable point is that healthcare data has been recently identified as a prime example of big data. Undoubtedly, efficient use of healthcare resources has become a key factor in improving overall healthcare system. But for managing healthcare data and obtaining potential results, we need integration and sharing of data that ultimately demand the conc
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Shukla, Purvika. "Big Data: Healthcare Informatics." International Journal for Research in Applied Science and Engineering Technology V, no. XI (2017): 1147–59. http://dx.doi.org/10.22214/ijraset.2017.11170.

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Sadiku, Matthew N. O. "Big Data in Healthcare." International Journal for Research in Applied Science and Engineering Technology 7, no. 9 (2019): 1165–68. http://dx.doi.org/10.22214/ijraset.2019.9167.

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Arvind, Uttiramerur. "Harnessing the Power of Big Data in Healthcare." Journal of Scientific and Engineering Research 9, no. 6 (2022): 67–72. https://doi.org/10.5281/zenodo.11487676.

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The amount of data that is available to us now is significantly increasing, which is changing the clinical research environment. The volume, velocity, and diversity of big data are beginning to significantly affect clinical trial accuracy and efficiency. Clinical research has advanced more quickly thanks to the use of large datasets that include a variety of information, including genetic data and electronic health records. Additionally, patients have benefitted from more individualized medical care that is catered to their specific requirements. In order to better understand the complex role
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Pramanik, Pijush Kanti Dutta, Saurabh Pal, and Moutan Mukhopadhyay. "Big Data and Big Data Analytics for Improved Healthcare Service and Management." International Journal of Privacy and Health Information Management 8, no. 1 (2020): 13–51. http://dx.doi.org/10.4018/ijphim.2020010102.

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Like other fields, the healthcare sector has also been greatly impacted by big data. A huge volume of healthcare data and other related data are being continually generated from diverse sources. Tapping and analysing these data, suitably, would open up new avenues and opportunities for healthcare services. In view of that, this paper aims to present a systematic overview of big data and big data analytics, applicable to modern-day healthcare. Acknowledging the massive upsurge in healthcare data generation, various ‘V's, specific to healthcare big data, are identified. Different types of data a
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Asri, Hiba, Hajar Mousannif, and Hassan Al Moatassime. "Big Data Analytics in Healthcare." International Journal of Distributed Systems and Technologies 10, no. 4 (2019): 45–58. http://dx.doi.org/10.4018/ijdst.2019100104.

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Sensors and mobile phones shine in the Big Data area due to their capabilities to retrieve a huge amount of real-time data; which was not possible previously. In the specific field of healthcare, we can now collect data related to human behavior and lifestyle for better understanding. This pushed us to benefit from such technologies for early miscarriage prediction. This research study proposes to combine the use of Big Data analytics and data mining models applied to smartphones real-time generated data. A K-means data mining algorithm is used for clustering the dataset and results are transm
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Ryu, Seewon, and Tae-Min Song. "Big Data Analysis in Healthcare." Healthcare Informatics Research 20, no. 4 (2014): 247. http://dx.doi.org/10.4258/hir.2014.20.4.247.

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Kim, Ha-Na. "Use of Healthcare Big Data." Korean Journal of Family Practice 7, no. 3 (2017): 307. http://dx.doi.org/10.21215/kjfp.2017.7.3.307.

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Dissertations / Theses on the topic "Big data in healthcare"

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Castaño, Martínez María, and Elizabeth Johnson. "Communicating big data in the healthcare industry." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-96251.

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In recent years nearly every aspect of how we function as a society has transformed from analogue to digital. This has spurred extraordinary change and acted as a catalyst for technology innovation, as well as big data generation. Big data is characterized by its constantly growing volume, wide variety, high velocity, and powerful veracity. With the emergence of COVID-19, the global pandemic has demonstrated the profound impact, and often dangerous consequences, when communicating health information derived from data. Healthcare companies have access to enormous data assets, yet communicating
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Mohamed, M. (Mahmoud). "Platforms for big data business models in the healthcare context." Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201906052419.

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Abstract. The profitability of the business opportunity is defined by the level of owned data and its insights to the business organization. However, the existing literature has not identified how to link between different business models in the data-oriented systems. The previous research efforts focused on the technical aspects of data including data monetization, clustering, and data lifecycle. The purpose of this research is to understand how to link big data and business model thinking in the healthcare context. The main argument of this study provides a novel way to the modularity in the
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Mgudlwa, Sibulela. "A big data analytics framework to improve healthcare service delivery in South Africa." Thesis, Cape Peninsula University of Technology, 2018. http://hdl.handle.net/20.500.11838/2877.

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Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2018.<br>Healthcare facilities in South Africa accumulate big data, daily. However, this data is not being utilised to its full potential. The healthcare sector still uses traditional methods to store, process, and analyse data. Currently, there are no big data analytics tools being used in the South African healthcare environment. This study was conducted to establish what factors hinder the effective use of big data in the South African healthcare environment. To fulfil the objectives of this research, qualita
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Nováková, Martina. "Analýza Big Data v oblasti zdravotnictví." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-201737.

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This thesis deals with the analysis of Big Data in healthcare. The aim is to define the term Big Data, to acquaint the reader with data growth in the world and in the health sector. Another objective is to explain the concept of a data expert and to define team members of the data experts team. In following chapters phases of the Big Data analysis according to methodology of EMC2 company are defined and basic technologies for analysing Big Data are described. As beneficial and interesting I consider the part dealing with definition of tasks in which Big Data technologies are already used in he
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Pšurný, Michal. "Big data analýzy a statistické zpracování metadat v archivu obrazové zdravotnické dokumentace." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-316821.

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This Diploma thesis describes issues of big data in healthcare focus on picture archiving and communication system. DICOM format are store images with header where it could be other valuable information. This thesis mapping data from 1215 studies.
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Jonsson, Hanna, and Luyolo Mazomba. "Revenue Generation in Data-driven Healthcare : An exploratory study of how big data solutions can be integrated into the Swedish healthcare system." Thesis, Umeå universitet, Företagsekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-161384.

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Abstract The purpose of this study is to investigate how big data solutions in the Swedish healthcare system can generate a revenue. As technology continues to evolve, the use of big data is beginning to transform processes in many different industries, making them more efficient and effective. The opportunities presented by big data have been researched to a large extent in commercial fields, however, research in the use of big data in healthcare is scarce and this is particularly true in the case of Sweden. Furthermore, there is a lack in research that explores the interface between big data
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Jamthe, Anagha. "Mitigating interference in Wireless Body Area Networks and harnessing big data for healthcare." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1445341798.

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Saenyi, Betty. "Opportunities and challenges of Big Data Analytics in healthcare : An exploratory study on the adoption of big data analytics in the Management of Sickle Cell Anaemia." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-42864.

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Background: With increasing technological advancements, healthcare providers are adopting electronic health records (EHRs) and new health information technology systems. Consequently, data from these systems is accumulating at a faster rate creating a need for more robust ways of capturing, storing and processing the data. Big data analytics is used in extracting insight form such large amounts of medical data and is increasingly becoming a valuable practice for healthcare organisations. Could these strategies be applied in disease management? Especially in rare conditions like Sickle Cell Dis
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Wang, Mengyuan. "The way of chinese medical reform : new trends in the era of the “internet+” and big data." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/18585.

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Mestrado em Desenvolvimento e Cooperação Internacional<br>A China é um país com uma população imensa, com recursos médicos insuficientes e distribuição desigual. Portanto, existem muitos problemas no serviço de saúde. Devido ao desenvolvimento atrasado do sistema médico, a qualidade dos recursos médicos é baixa, o custo é alto e a eficiência dos serviços médicos é baixa. Um dos principais fatores explicativos dessa situação é a falta de apoio do governo e seguro médico imperfeito. Para resolver esse problema, o governo começou a reformar o sistema de segurança médica. Desde a reforma do seguro
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Ramadoss, Balaji. "Ontology Driven Model for an Engineered Agile Healthcare System." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5110.

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Healthcare is in urgent need of an effective way to manage the complexity it of its systems and to prepare quickly for immense changes in the economics of healthcare delivery and reimbursement. Centers for Medicare & Medicaid Services (CMS) releases policies affecting inpatient and long-term care hospitals policies that directly affect reimbursement and payment rates. One of these policy changes, a quality-reporting program called Hospital Inpatient Quality Reporting (IQR), will effect approximately 3,400 acute-care and 440 long-term care hospitals. IQR sets guidelines and measures that will c
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Books on the topic "Big data in healthcare"

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Amirian, Pouria, Trudie Lang, and Francois van Loggerenberg, eds. Big Data in Healthcare. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62990-2.

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Ebeling, Mary F. E. Healthcare and Big Data. Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/978-1-137-50221-6.

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Kulkarni, Anand J., Patrick Siarry, Pramod Kumar Singh, et al., eds. Big Data Analytics in Healthcare. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-31672-3.

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Shen, Bairong, ed. Healthcare and Big Data Management. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6041-0.

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Househ, Mowafa, Andre W. Kushniruk, and Elizabeth M. Borycki, eds. Big Data, Big Challenges: A Healthcare Perspective. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06109-8.

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Wang, Baoying, Ruowang Li, and W. Perrizo. Big data analytics in bioinformatics and healthcare. Medical Information Science Reference, 2015.

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Natarajan, Prashant, John C. Frenzel, and Detlev H. Smaltz. Demystifying Big Data and Machine Learning for Healthcare. CRC Press, 2017. http://dx.doi.org/10.1201/9781315389325.

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Langkafel, Peter, ed. Big Data in Medical Science and Healthcare Management. DE GRUYTER, 2015. http://dx.doi.org/10.1515/9783110445381.

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Langkafel, Peter, ed. Big Data in Medical Science and Healthcare Management. DE GRUYTER, 2015. http://dx.doi.org/10.1515/9783110445749.

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Saxena, Ankur, Nicolas Brault, and Shazia Rashid. Big Data and Artificial Intelligence for Healthcare Applications. Edited by Ankur Saxena, Nicolas Brault, and Shazia Rashid. CRC Press, 2021. http://dx.doi.org/10.1201/9781003093770.

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Book chapters on the topic "Big data in healthcare"

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Karthika, D., and K. Kalaiselvi. "Big Data." In Intelligent Healthcare. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67051-1_3.

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Amirian, Pouria, Francois van Loggerenberg, and Trudie Lang. "Big Data and Big Data Technologies." In Big Data in Healthcare. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62990-2_3.

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Paganoni, Maria Cristina. "Big Data and Healthcare." In Framing Big Data. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16788-2_3.

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Manoj Kumar, M. V., B. S. Prashanth, Aditya Shastry, H. A. Sanjay, and H. R. Sneha. "Healthcare Data Visualization." In Studies in Big Data. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0415-7_9.

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Ramírez, Margarita Ramírez, Hilda Beatriz Ramírez Moreno, and Esperanza Manrique Rojas. "Big Data in HealthCare." In Studies in Big Data. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8476-8_7.

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Rajbhandari, Sachet, Archana Singh, and Mamta Mittal. "Big Data in Healthcare." In International Conference on Innovative Computing and Communications. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2354-6_28.

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Kumar, Rajesh, Hardik Daga, and Latika Choudhary. "Big Data and Healthcare." In Demystifying Big Data Analytics for Industries and Smart Societies. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9781003330875-7.

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Husain, Mohd Shahid, Mohammad Zunnun Khan, and Tamanna Siddiqui. "Big Data for Healthcare." In Big Data Concepts, Technologies, and Applications. Auerbach Publications, 2023. http://dx.doi.org/10.1201/9781003441595-12.

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Vishnoi, Sushant Kumar, Naveen Virmani, Divya Pant, Naveen Virmani, and Ankit Garg. "Big Data in Healthcare." In Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics. CRC Press, 2022. http://dx.doi.org/10.1201/9781003217107-12.

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Shi, Yong. "Healthcare Applications." In Advances in Big Data Analytics. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-3607-3_11.

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Conference papers on the topic "Big data in healthcare"

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Sharma, Brijesh Kumar, Khel Prakash Jayant, Purvi Pujari, Devendra Vikram, Manish Saraswat, and Kajol Kathuria. "Big Data Analytics for Healthcare Resource Allocation." In 2025 International Conference on Pervasive Computational Technologies (ICPCT). IEEE, 2025. https://doi.org/10.1109/icpct64145.2025.10941482.

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Prakash, Saurabh, Uddhav T. Kumbhar, Satish V. Kakade, G. Anitha, and Arjun Mittal. "Integration of Data Mining and Big Data Analytics in Healthcare." In 2024 International Conference on Healthcare Innovations, Software and Engineering Technologies (HISET). IEEE, 2024. http://dx.doi.org/10.1109/hiset61796.2024.00075.

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Jiang, Emily, Alice Chen, Irene Tenison, and Lalana Kagal. "MediRAG: Secure Question Answering for Healthcare Data." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825604.

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Kechadi, M.-Tahar. "Healthcare Big Data." In the International Conference. ACM Press, 2016. http://dx.doi.org/10.1145/3010089.3010143.

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Adenuga, Kayode I., Idris O. Muniru, Fatai I. Sadiq, Rahmat O. Adenuga, and Muhammad J. Solihudeen. "Big Data in Healthcare." In ICSIE '19: 2019 8th International Conference on Software and Information Engineering. ACM, 2019. http://dx.doi.org/10.1145/3328833.3328841.

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Rajkumar, Siddhant, and Yasha Hasija. "Big data in healthcare." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING APPLICATIONS-21 (ICCICA-21). AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0077737.

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Rahman, Fuad, Marvin Slepian, and Ari Mitra. "A novel big-data processing framwork for healthcare applications: Big-data-healthcare-in-a-box." In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7841018.

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Sterling, Mark. "Situated big data and big data analytics for healthcare." In 2017 IEEE Global Humanitarian Technology Conference (GHTC). IEEE, 2017. http://dx.doi.org/10.1109/ghtc.2017.8239322.

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Krause, P. "Big Healthcare Data: Realising the Promise." In Data Analytics 2014: The Rising Role of Big Data. Institution of Engineering and Technology, 2014. http://dx.doi.org/10.1049/ic.2014.0029.

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Wang, Shu-Lin, I.-En Chiang Honours, Alex Kuo, and Jing-Ya Lin. "Mobile Emotion Healthcare System Applying Sentiment analysis." In 2022 IEEE International Conference on Big Data (Big Data). IEEE, 2022. http://dx.doi.org/10.1109/bigdata55660.2022.10021053.

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Reports on the topic "Big data in healthcare"

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Bonnett, Michaela, Meaghan Kennedy, Odiraa Okala, and Teri Garstka. Precision Public Health: Empowering Communities with Hyperlocal Data for Targeted Interventions and Improved Outcomes. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/sktq6431.

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Background Precision public health is an effective strategy for reaching the last mile in service delivery, but is frequently hampered by its dependence on unattainable data standards and the non-transferability of the solutions designed. This paper proposes a five-part system involving 1) dynamic data governance, 2) hyperlocal community data, 3) data synthesis and analysis, 4) the design and implementation of precision interventions, and 5) correlation between community data and traditional outcome data. Recent studies of community network data have found the connectedness of communities to b
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Zwitter, Andrej J., and Amelia Hadfield. Governing Big Data. Librello, 2014. http://dx.doi.org/10.12924/pag2014.02010001.

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Gawade, Rushikesh. Big data and big dollars are changing cricket. Edited by Chris Bartlett. Monash University, 2023. http://dx.doi.org/10.54377/783a-d051.

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Gildea, Timothy R. Big Data health Physics. Office of Scientific and Technical Information (OSTI), 2020. http://dx.doi.org/10.2172/1603973.

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Goldstein, Itay, Chester Spatt, and Mao Ye. Big Data in Finance. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28615.

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Big data en salud digital. Chair Alberto Urueña López and José María San Segundo Encinar. ONTSI : Fundación Vodafone España, 2017. http://dx.doi.org/10.30923/5896-8.

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Alewijn, M. Big data - Banana origin determination. Wageningen Food Safety Research, 2020. http://dx.doi.org/10.18174/516096.

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Doucet, Rachel A., Deyan M. Dontchev, Javon S. Burden, and Thomas L. Skoff. Big Data Analytics Test Bed. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada589903.

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Farboodi, Maryam, Roxana Mihet, Thomas Philippon, and Laura Veldkamp. Big Data and Firm Dynamics. National Bureau of Economic Research, 2019. http://dx.doi.org/10.3386/w25515.

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Li, Junteng. ADL Data Capturing System: A Big Data Approach. Iowa State University, 2019. http://dx.doi.org/10.31274/cc-20240624-116.

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