Title :
An Intelligent Hybrid Hemodynamic Data Monitoring for Post-Cardiac Surgical Patients
Author :
Rahman, Alias Abdul ; Rabiah, A.K. ; Nasir, M.S. ; Lilly, S.A. ; Zamrin, M.D. ; Joanna, O.S.M.
Author_Institution :
Fac. of Comput. Sci. & Inf. Technol., Univ. Putra Malaysia, Serdang, Malaysia
Abstract :
Cardiothoracic Intensive Care Units (CICU) patients require vigilant watchful and very strict monitoring of their conditions in real time. Accurate observation is required through bedside monitoring devices which generates massive amounts of data. Such a countless of data which reflect the cardiovascular system and its physiological components pose a lot of difficulties, challenges and is time consuming to the clinicians and health care professionals who are required to interpret and analyze such an overload of information which could cause errors in patient care which could prove fatal. Patients admitted to CICU are characterized by periods of hemodynamic instability and management of these patients requires prompt and accurate therapeutic diagnosis in order to avoid serious complications. This paper describes the design and implementation of an Intelligent Hybrid Hemodynamic Data Monitoring (IHHDM) to overcome such difficulties and to help medical experts in making appropriate decisions. The system has the capability to perform the functions which are normally associated with human intelligence in providing accurate diagnosis and to determine the suitable therapy and specific dosages of drugs administered to the patients. This will increase the quality and the efficiency of the working environment in the CICU, reduce medical errors which may result in suboptimal patient care, and enhance the usefulness of medical sciences.
Keywords :
cardiology; patient care; patient diagnosis; patient monitoring; surgery; Intelligent Hybrid Hemodynamic Data Monitoring; cardiothoracic intensive care units patients; cardiovascular system; clinicians; drugs; health care professionals; hemodynamic instability; intelligent hybrid hemodynamic data monitoring; medical sciences; monitoring devices; patient care; patient management; physiological components; post-cardiac surgical patients; therapeutic diagnosis; Cardiothoracic Intensive Care Units (CICU); Cardiovascular System (CVS); Case Base Reasoning(CBR); Case-Base Memory; Data Minig (DM); Hemodynamic Data; Intelligent Hybrid Hemodynamic Data Monitoring (IHHDM);
Conference_Titel :
Advanced Computer Science Applications and Technologies (ACSAT), 2012 International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4673-5832-3
DOI :
10.1109/ACSAT.2012.83