Ontology-based Text Mining for eHealth Data


Program                     Microsoft Research Asia e-Health Theme Program

Title                            Ontology-based Text Mining for eHealth Data

Duration                     March 2011 - February 2012 (1 Year)

Principal Investigator Prof. Sungyoung Lee (PhD)

Participants                Zeeshan Pervez (PhD Student), Manhyung Han (PhD Student), Iram Fatimah (PhD Student),
                                      Asad Masood Khattak (PhD Student), Muhammad Bilal Amin (PhD Student),
                                      Wajahat Ali Khan (PhD Student), PhamThe Anh (MS. Student), Ji Su Oh (MS. Student)

Project Overview

The “Ontology-based Text Mining for eHealth Data” provides ubiquitous system that is able to provide initial treatment, alerts, suggestions, recommendations for a broad spectrum of patient’s illnesses and injuries in general. In particular, here these services are provided to Diabetes patients. As some of the symptoms of diabetes may be life-threatening and require immediate attention and response of caregivers. For this purpose an interactive and ubiquitous eHealthcare system can fulfill the needs.

For an eHealthcare system, to manage the stream of patients efficiently, accurately, and quickly, hospitals require a broad range interactive technologies, measurement technologies, and tools. That helps support the workflow, from taking vital signs to making advanced diagnosis, alerts, suggestions, recommendations, and further care planning. Our Project is particularly targeted to provide these services while using the cloud platform provided by  Microsoft Azure environment.

Project Objectives

Project Deployment