Recognizing unstructured EMR - Al Sheref, Fahad;Abdulgaber, Sayed;Bushnaq, Hussien
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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.…mehr

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Produktbeschreibung
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%.
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Autorenporträt
Fahad is an assistant professor of information systems department in Beni-Suef University, Egypt. He was born in sohag 1983, and finished his Ph.D. in information systems in 2015. Also he is a consultant in several governmental projects and companies.