Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare
Recently, the rate of data generation has reached unprecedented levels, leading to a huge amount of data volume. In addition, modern-day computing systems generate data in diverse formats, ranging from unstructured to structured and semi-structured. As technological advancements experience exponenti...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10314483/ |
| _version_ | 1827700503020044288 |
|---|---|
| author | Fatima Hussain Muhammad Nauman Abdullah Alghuried Adi Alhudhaif Nadeem Akhtar |
| author_facet | Fatima Hussain Muhammad Nauman Abdullah Alghuried Adi Alhudhaif Nadeem Akhtar |
| author_sort | Fatima Hussain |
| collection | DOAJ |
| description | Recently, the rate of data generation has reached unprecedented levels, leading to a huge amount of data volume. In addition, modern-day computing systems generate data in diverse formats, ranging from unstructured to structured and semi-structured. As technological advancements experience exponential growth, novel trends, and strategies are emerging in the field of Big Data to enhance data quality and derive valuable insights, particularly in industries like healthcare. The primary objective of this study is to investigate the challenges and applications of Big Data in healthcare, with a specific focus on improving clinical decision-making. By analyzing 185 papers published between 2012 and 2023, this review article aims to provide a comprehensive overview of the techniques and methods employed in utilizing Big Data Analytics in the healthcare domain. Furthermore, the article aspires to assist the research community in identifying suitable approaches and methodologies for their healthcare-related studies. |
| first_indexed | 2024-03-10T14:13:05Z |
| format | Article |
| id | doaj.art-cecf2505aa674ef083590c6f2c0d6a99 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-10T14:13:05Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-cecf2505aa674ef083590c6f2c0d6a992023-11-21T00:01:31ZengIEEEIEEE Access2169-35362023-01-011112781712783610.1109/ACCESS.2023.333203010314483Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in HealthcareFatima Hussain0Muhammad Nauman1https://orcid.org/0000-0003-3173-2549Abdullah Alghuried2Adi Alhudhaif3https://orcid.org/0000-0002-7201-6963Nadeem Akhtar4https://orcid.org/0000-0003-2475-5590Department of Software Engineering, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, Punjab, PakistanDepartment of Software Engineering, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, Punjab, PakistanDepartment of Industrial Engineering, Faculty of Engineering, University of Tabuk, Tabuk, Saudi ArabiaDepartment of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi ArabiaDepartment of Software Engineering, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, Punjab, PakistanRecently, the rate of data generation has reached unprecedented levels, leading to a huge amount of data volume. In addition, modern-day computing systems generate data in diverse formats, ranging from unstructured to structured and semi-structured. As technological advancements experience exponential growth, novel trends, and strategies are emerging in the field of Big Data to enhance data quality and derive valuable insights, particularly in industries like healthcare. The primary objective of this study is to investigate the challenges and applications of Big Data in healthcare, with a specific focus on improving clinical decision-making. By analyzing 185 papers published between 2012 and 2023, this review article aims to provide a comprehensive overview of the techniques and methods employed in utilizing Big Data Analytics in the healthcare domain. Furthermore, the article aspires to assist the research community in identifying suitable approaches and methodologies for their healthcare-related studies.https://ieeexplore.ieee.org/document/10314483/Big data analyticshealthcare industrymedical big databig data managementreview study |
| spellingShingle | Fatima Hussain Muhammad Nauman Abdullah Alghuried Adi Alhudhaif Nadeem Akhtar Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare IEEE Access Big data analytics healthcare industry medical big data big data management review study |
| title | Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare |
| title_full | Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare |
| title_fullStr | Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare |
| title_full_unstemmed | Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare |
| title_short | Leveraging Big Data Analytics for Enhanced Clinical Decision-Making in Healthcare |
| title_sort | leveraging big data analytics for enhanced clinical decision making in healthcare |
| topic | Big data analytics healthcare industry medical big data big data management review study |
| url | https://ieeexplore.ieee.org/document/10314483/ |
| work_keys_str_mv | AT fatimahussain leveragingbigdataanalyticsforenhancedclinicaldecisionmakinginhealthcare AT muhammadnauman leveragingbigdataanalyticsforenhancedclinicaldecisionmakinginhealthcare AT abdullahalghuried leveragingbigdataanalyticsforenhancedclinicaldecisionmakinginhealthcare AT adialhudhaif leveragingbigdataanalyticsforenhancedclinicaldecisionmakinginhealthcare AT nadeemakhtar leveragingbigdataanalyticsforenhancedclinicaldecisionmakinginhealthcare |