View Article

Abstract

Predictive analytics plays a vital role in transforming healthcare by improving patient care, reducing costs, and optimizing resource allocation. As technology continues to advance and healthcare systems become more data- driven, the benefits of predictive analytics are likely to expand, contributing to better healthcare outcomes for individuals and populations alike. Predictive analytics is transforming the healthcare landscape by enhancing early disease detection and prevention. By harnessing the power of data and artificial intelligence, healthcare providers can offer more personalized, effective, and cost-efficient care. While challenges exist, the potential to save lives and Improve overall healthcare outcomes. Makes predictive analytics an Indispensable tool in the fight against diseases. As technology continues to advance, the impact of predictive analytics in early disease detection and prevention will only become more pronounced, reshaping the future of healthcare In the dynamic landscape of healthcare, where innovation is the compass guiding us forward. It is al journey marked by innovation, data-driven insights, and the relentless pursuit of proactive healthcare practices that hold the potential to usher in a new era of disease- prevention and early intervention. Through this review, we aim to illuminate the path ahead, recognizing both the remarkable accomplishments and the challenges that lie on the horizon as we hamess the power of predictive analytics to transform the future of healthcare. These models learn patterns and relationships in the data. In the realm of medical imaging, Al-powered tools are augmenting the capabilities of healthcare professionals. Predictive analytics in healthcare refers to the analysis of current and historical healthcare data that allows healthcare professionals to find opportunities to make more effective and more efficient operational and clinical decisions, predict trends, and even manage the spread of diseases. The proposed system offers a broad disease prognosis based on patient’s symptoms by using the machine learning algorithms such as convolutional neural network (CNN) for automatic feature extraction and disease prediction and K-nearest neighbor (KNN) for distance calculation to find the exact match in the data set and the final disease prediction outcome. A collection of disease symptoms has been performed for the preparation of the data set along with the person’s living habits, and details related to doctor consultations are taken into account in this general disease prediction. Finally, a comparative study of the proposed system with various algorithms such as Naïve Bayes, decision tree.

Keywords

Predictive Analytic

Reference

  1. Abouelmehdi K, Beni-Hessane A, Khaloufi H. Big healthcare data: preserving security and privacy. J Big Data, 2018.
  2. Agrawal A, Choudhary A. Health services data: big data analytics for deriving predictive healthcare insights. Health Serv Eval, 2019.
  3. Al Mayahi S, Al-Radi A, Tarhini A. Exploring the potential benefits of big data analytics in providing smart healthcare. In: Miraz MH, Excell P, Ware A, Ali M, Soomro S, editors. Emerging technologies in computing first international conference, ¡CETIC 2018, proceedings (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). Cham: Springer, 2018; 247-58. 10.1007/978-3-319-95450- 9_21.
  4. B.Carter P. Big data analytics; future architectures,Skills and roadmaps for the CIO: in white paper, IDC sponsored by SAS, 2011; 1-16.
  5. Bi 7, Cochran D. Big data analytics with applications. 1 Manag Anal, 2014; 1(4): 249 265.
  6. Bollier D, Firestone CM. The promise and peril of big data. Washington, DC Aspen Institute, Communications and Society Program, 2010; 1 66.
  7. Bartu K, Batko K. Lorek P. Business intelligence systems: baniers during implementation. In: Jablonski M. editor. Strategic performance management new concept and contemporary trends, New York Nova Science Publishers, 2017; 299 327.
  8. Bartus K. Butko K. Lorek P. Diagnoza wykorzystania big data w organizacjach-wybrane wyniki bada? Informatyka Ekonomiczna 2017: 3(45): 9-20.
  9. Bartus K. Butko K. Lorek P. Diagnoza wykorzystania big data w organizacjach-wybrane wyniki bada? Informatyka Ekonomiczna 2017: 3(45): 9-20.
  10. Bartus K, Batko K, Lorck P. Wykorzystanie rozwi?za? business intelligence. competitive intelligence i hig data w przedsi?biorstwach województwa ?l?skiego. Przegl?d Organizacji, 2018;2:33-39.
  11. Bainbridge M. Big data challenges for clinical and precision medicine. In: Househ M, Kushniruk A, Borycki E. editors. Big data, big challenges: a healthcare perspective: background, issues, solutions and research directions. Cham: Springer, 2019; 17- 31.
  12. Boerma T, Requejo J, Victora CG, Amourou A, Asha G, Agyepong 1, Borghi J. Countdown to 2030: tracking progress towards universal coverage for reproductive, maternal, newborn, and child health,Lancet, 2018; 391(10129): 1538-1548.
  13. Bartus K. Balko K. Lorek P. Mo?liwo?ci wykorzystania Big Data w ochronie zdrowia.Roczniki Kolegium Analiz Ekonomicznych, 2016; 42: 267-282.
  14. Bose R. Competitive intelligence process and tools for intelligence analysis. Ind Manag Data Syst 2008; 108(4): 510-528.
  15. Castro EM, Van Regenmortel T. Vanhaecht K, Sermeus W. Van Hecke A. Patient empowerment, patient participation and patient-centeredness in hospital care: a concept analysis based on a literature review. Patient Educ Couns, 2016; 99(12): 1923- 1939.
  16. Chen H. Chiang RH. Storey VC Business intelligence and analytics from big data to big impact. MIS Q, 2012; 36(4): 1165-1188.
  17. Chen CP, Zhang CY. Data-intensive applications, challenges, techniques and technologies: a survey on big data. Inf Sci, 2014; 275: 314-347.
  18. Gupta D., Khare S., Aggarwal A. A method to predict diagnostic codes for chronic diseases using machine learning techniques. Proceedings of the 2016 International Conference on Computing, Communication and Automation (ICCCA); April 2016; Greater Noida, India. IEEE; pp. 281–287.
  19. Hossain Md E. Camperdown NSW, Australia: University of Sydney; 2020. Predictive Modelling of the Comorbidity of Chronic Diseases: A Network and Machine Learning Approach. PhD Thesis.[Google scholar]
  20. Ismail A., Salem M. L., Elkholy A., Elmashad W., Gomaa A., Ali M. In-silico analysis of protein receptors contributing to SARS- COV-2 high infectivity. Information Sciences Letters . 2021;10(3):561–570.[Google scholar]
  21. Induja S. N., Raji C. G. Computational methods for predicting chronic disease in healthcare communities. Proceedings of the 2019 International Conference on Data Science and Communication (IconDSC); March 2019; Bangalore, India. IEEE; pp. 1–6.
  22. Zhang X., Zhao H., Zhang S., Li R. A novel deep neural network model for multi-label chronic disease prediction. Frontiers in Genetics . 2019;10:p. 351.

Photo
Hariom Rajput
Corresponding author

Yeshwant Niwas Rd, Lantern Square, Yeshwant Colony, Indore, Madhya Pradesh

Photo
Sanoop Kumar Tiwari
Co-author

Yeshwant Niwas Rd, Lantern Square, Yeshwant Colony, Indore, Madhya Pradesh

Photo
Co-author

Hariom Rajput*, Sanoop Kumar Tiwari, Detection Of Diseases And Predictive Analytic, Int. J. in Pharm. Sci., 2023, Vol 1, Issue 11, 180-191. https://doi.org/10.5281/zenodo.10084620

More related articles
Review Of Monkeypox Virus :Symptoms ,Pathogenesis ...
Pratiksha A. Udawant, Sabafarin Shaikh, Khare Komal, Mayur S. Bho...
A Review On Giloy: One Plant Many Roles...
Sarthak Ramesh Yadav, Vaishali. V. Kadam, Bhagyashri borade, Vais...
Development And Validation Of HPLC Method For Esti...
Sanket Hire, Smita Aher, Rushikesh Bachhav, ...
A Detailed Analysis Of Alzheimer's Disease Pathophysiology: The Influence Of Oxi...
Arnab Roy, Manav Kumar, Alok Kumar , Kajal Kumari , Priyanka Kumari, Shweta Kumari, Divya Roshni Pan...
A Review On : Fast Dissolving Oral Thin Film...
Pote Ashwini.B, Zarad Snehal, Ashok Dalimbe , ...
A Review On Liposomes As Drug Delivery System...
Ayush S. Jaiswal, Rekha Gaukande, Gajanan Sanap, ...
Related Articles
Ayurvedic Remedies of Bacterial Meningitis...
Komal Ushir, Dinesh Rishipathak, Pragati Bhosale, Manisha Raut, ...
To Ensure Patient Safety In Bhaktivedanta Hospital & Research Institute By Conti...
Deepak Mali, Narendra Pande, Haripriya Tinani , Gajanan Ramtake, Ila Gosh , Kailas M., Sivaprasad G....
Advancing HIV Prevention: A Comprehensive Analysis Of PrEP's Efficacy, Adherence...
Manav Kumar, Kajal Kumari , Nahida Khatun, Sapna Kumari, Laxman Kumar Mahto, Divya Roshni Panna, Bin...
Review Of Monkeypox Virus :Symptoms ,Pathogenesis ,Diagnosis And Treatment...
Pratiksha A. Udawant, Sabafarin Shaikh, Khare Komal, Mayur S. Bhosle, Sushmita Chavan, ...
More related articles
Review Of Monkeypox Virus :Symptoms ,Pathogenesis ,Diagnosis And Treatment...
Pratiksha A. Udawant, Sabafarin Shaikh, Khare Komal, Mayur S. Bhosle, Sushmita Chavan, ...
A Review On Giloy: One Plant Many Roles...
Sarthak Ramesh Yadav, Vaishali. V. Kadam, Bhagyashri borade, Vaishnavi walhekar, ...
Review Of Monkeypox Virus :Symptoms ,Pathogenesis ,Diagnosis And Treatment...
Pratiksha A. Udawant, Sabafarin Shaikh, Khare Komal, Mayur S. Bhosle, Sushmita Chavan, ...
A Review On Giloy: One Plant Many Roles...
Sarthak Ramesh Yadav, Vaishali. V. Kadam, Bhagyashri borade, Vaishnavi walhekar, ...