الفهرس 
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Abstract
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 Medical Records (EMR) management system. EMR implementation and adoption face different barriers that slow down the deployment of the EMR systems in different organizations.
Data entry, unstructured clinical data, and new physician workflow adoption represent the focusing barriers of this research. Text mining and natural language processing are the suggested techniques to deal with these barriers. Clinical reports contain a lot of unstructured data and it is too difficult to manage this data and generate useful reports and graphs. The main objective of this research is converting this unstructured data into stnrctured data without undue physical actions (such as menu use, mouse clicks, and so on), or excessive mental effort (what the clinician should click to perform a given task or to enter diagnoses, and so on).
The developed solution is tested and verified by four clinical specialists. They approved its success in physician’s handwriting conversion into stnrctured EMR 91.36 % of the studied cases.