Recognizing unstructured EMR | Recognizing the Electronic Medical Record Data from Unstructured Medical Data Using Visual Text Mining Techniques

Fahad Al Sheref (u. a.)

ISBN 10: 6202511834 / ISBN 13: 9786202511834

Published by LAP LAMBERT Academic Publishing, 2020

About this Item

Recognizing unstructured EMR | Recognizing the Electronic Medical Record Data from Unstructured Medical Data Using Visual Text Mining Techniques | Fahad Al Sheref (u. a.) | Taschenbuch | 128 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786202511834 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Seller Inventory # 118209745

Bibliographic Details

• Title: Recognizing unstructured EMR | Recognizing the Electronic Medical Record Data from Unstructured Medical Data Using Visual Text Mining Techniques
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2020
• Language: English
• ISBN 10: 6202511834
• ISBN 13: 9786202511834
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 9D millimeters 220 millimeters width by 150 millimeters height by 9 millimeters depth
• Weight: 209 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Computer systems and communication technologies made a strong and influential presence in the different fields of medicine. The cornerstone of a functional medical information system is the Electronic Health Records (EHR) management system. EHR implementation and adoption face different barriers that slow down its deployment in different organizations. This research focuses on resolving the most public barriers, which are data entry, unstructured clinical data modifying the physician work flow. This research proposed a solution, which use Text mining and Natural language processing techniques. This solution tested and verified in four real-world clinical organizations. The suggested solution proved correcteness and perciseness with 91.88%.