Data Mining and Knowledge Discovery : Applications , Techniques , Challenges and Process Models in Healthcare
@inproceedings{ElSappagh2013DataMA, title={Data Mining and Knowledge Discovery : Applications , Techniques , Challenges and Process Models in Healthcare}, author={Shaker H. Ali El-Sappagh and Samir El-Masri and Alaa Eldin M. Riad and Mohammed M Elmogy}, year={2013} }
Many healthcare leaders find themselves overwhelmed with data, but lack the information they need to make right decisions. Knowledge Discovery in Databases (KDD) can help organizations turn their data into information. Organizations that take advantage of KDD techniques will find that they can lower the healthcare costs while improving healthcare quality by using fast and better clinical decision making. In this paper, a review study is done on existing data mining and knowledge discovery…
13 Citations
Data Mining In Healthcare: A Survey of Techniques and Algorithms with Its Limitations and Challenges
- Computer Science, Medicine
- 2013
The large amount of data in healthcare industry is a key resource to be processed and analyzed for knowledge extraction, and it is necessary to identify and evaluate the most common data mining algorithms implemented in modern healthcare services.
Knowledge Discovery from Healthcare Electronic Records for Sustainable Environment
- Medicine, Computer ScienceSustainability
- 2021
An overview of the data mining techniques used for knowledge discovery in medical records is proposed and a case study of discovering knowledge with the help of three data mining Techniques is demonstrated: association analysis, sequential pattern mining and clustering.
A Review of Knowledge Based System in Healthcare Using Text Mining
- Computer Science
- 2015
This research paper talks about the text mining and issues of textual data for effective knowledge discovery and is also intended towards the application and benefits of text mining in healthcare.
Discussing the Role of Data Mining in Development of Evidence Based Decision Support System for e-Healthcare
- Medicine, Computer Science
- 2017
The role of data mining in developing a decision support system is discussed and a case study of EBM integrated HMIS is presented.
Data Mining technology as a tool for supporting analytical decision making process in Health Information Management System (HIMS)
- Medicine, Computer ScienceAmerican Journal of Agricultural Science, Engineering and Technology
- 2021
This paper presents the usefulness of data mining technology in Hospital Information Management System (HIMS) and offers capabilities to increase the productivity of medical personnel, analyze care outcomes, lower healthcare costs, improve healthcare quality by using fast and better clinical decision making and generally assist the strategic management mechanisms.
A Review on Leveraging Big Data Analytics in Health Care Sector for Enhanced Diagnosis and Competent Patient Health Care Monitoring System
- Medicine, Computer Science
- 2017
This paper proposes the conceptual architecture of BDA in healthcare sector and highlights the applications of Bda, its potential challenges and future directions in healthcare domain.
Applied machine learning classifiers for medical applications: Clarifying the behavioural patterns using a variety of datasets
- Computer Science2015 International Conference on Systems, Signals and Image Processing (IWSSIP)
- 2015
Five well-known supervised machine-learning classifiers were examined using five different real-world datasets with a range of attributes to present the classifiers capabilities and shortcomings under certain conditions and potentially provide a guidance or instructions to help health analysts and researchers to determine the most suitable classifier to address a particular medical-related decision making problem.
Data driven implementation to filter fraudulent medicaid applications
- Computer Science, MedicineIEEE SOUTHEASTCON 2014
- 2014
A data driven implementation using a layered architecture to filter fraudulent applications for Medicaid is proposed using a set of public and private databases which contain asset records of an individual.
Detection of Cardiovascular Disease Risk's Level for Adults Using Naive Bayes Classifier
- MedicineHealthcare informatics research
- 2016
A mining model using a naïve Bayes classifier that could detect cardiovascular disease and identify its risk level for adults and achieves good performance for risk level detection of cardiovascular disease is proposed.
Predicting the likelihood of heart failure with a multi level risk assessment using decision tree
- Medicine2015 Third International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE)
- 2015
A multi-level risk assessment of developing heart failure has been proposed, in which a five risk levels of heart failure can be predicted using C4.5 decision tree classifier.
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