Innovations in Healthcare Analytics: A Review of Data Mining Techniques
Shikha Bhardwaj1, Neeraj Bhargava2, Ritu Bhargava3
1Shikha Bhardwaj, Department of Computer Science, Mahatma Jyoti Rao Phoole University, Jaipur (R.J), India.
2Prof. Neeraj Bhargava, Department of Computer Science, M.D.S University, Ajmer (R.J), India.
3Dr. Ritu Bhargava, Sophia girls’ College, Ajmer (R.J), India.
Manuscript received on 15 April 2023 | Revised Manuscript received on 20 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 8-14 | Volume-13 Issue-2, May 2023 | Retrieval Number: 100.1/ijsce.B36090513223 | DOI: 10.35940/ijsce.B3609.0513223
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This review article provides an overview of the current state of data mining applications in healthcare, including case studies, challenges, and future directions. The article begins with a discussion of the role of data mining in healthcare, highlighting its potential to transform healthcare delivery and research. It then provides a comprehensive review of the various data mining techniques and tools that are commonly used in healthcare, including predictive modelling, clustering, and association rule mining. The article also discusses some key challenges associated with data mining in healthcare, such as data quality, privacy, and security, and suggests possible solutions. Finally, the article concludes with a discussion of the future directions of data mining in healthcare, highlighting the need for continued research and development in this field. The article emphasises the importance of collaboration between healthcare providers, data scientists, and policymakers to ensure that data mining is used ethically and effectively to improve patient outcomes and support evidence-based decision-making in healthcare.
Keywords: Data Mining; Health Care; SVM; ANN
Scope of the Article: Data Mining