• Corpus ID: 16092489

Data and Text Mining the Electronic Medical Record to Improve Care and to Lower Costs

  title={Data and Text Mining the Electronic Medical Record to Improve Care and to Lower Costs},
  author={Patricia B. Cerrito and John C. Cerrito},
This analysis uses data-mining techniques on an electronic medical record in the Emergency Department of a hospital to improve care while lowering costs. All patients' records for a 6-month period were examined, and records of those patients who had an initial complaint of shortness-of-breath were extracted. The data-mining techniques of transactional time series in the HPF procedure and the association rules in SAS® Enterprise MinerTM were used to examine the data. Patients' orders… 
Computerized sorting of electronic health care records using text mining
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Text Mining in Health Care Sector Techniques, Applications and Challenges
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    2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS)
  • 2021
This paper depicts/overlays the study of algorithms, tools and techniques involved in text mining for health care data.
Using text and visual mining to analyze clinical diagnosis records
Investigation of the analysis of free-textual clinical medical diagnosis documents with ICD-9 codes using state-of-the-art techniques from text and visual mining fields shows that ViSOM and SOM are helpful for organizational decision-making activities.
A Review : Electronic Medical Records ( EMR ) System for Clinical Data Storage at health centers
This paper reviews EMR implementation and EMR tools used in various hospitals in different countries, and identifies the benefits, limits and importance of EMR for clinical data storage and research.
Big Data in Healthcare: New Methods of Analysis
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Automated detection of follow-up appointments using text mining of discharge records.
Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.
Application of Knowledge Discovery in Database to Blood Cell Counter Data to Improve Quality Control in Clinical Pathology
  • D. Minnie, S. Srinivasan
  • Computer Science
    2011 Sixth International Conference on Bio-Inspired Computing: Theories and Applications
  • 2011
An application of the data preprocessing phase of the Knowledge Discovery in Databases (KDD) processes such as data cleaning, data selection and data transformation on the blood cell counter data to enhance the quality of the system is proposed.
SA 12-1-Data Mining Episode Groupers
This study uses data from a cohort of patients with heart problems and diabetes to develop a method to define sequential episodes of patient care and use decision trees to examine the relationship between treatment and outcome.
Clustering and Predictive Modeling of Patient Discharge Records with SAS ® Enterprise Miner TM
Cluster analysis of patient discharges improved the overall average square error of predictive models and distinguished predictors that were unique to patient segments.
Network Based Framework for Information Retrieval Using Feature Association with Improved Keyword Weighting Factor
In this study, a new paradigm for master defect record retrieval using network-based feature association (NBFA) is proposed and a new keyword weighting scheme is proposed to increase the relevance measure.