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Friday, August 6, 2010
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To model real time hemodynamic monitoring system for post operative cardiothoracic patients in CICU, and To develop intelligent Cardiothoracic ICU Hemodynamic Monitoring System
Group CACS
Research Background
Problem Statement:
There are none real time medical data collection and if exist it will prone to human error
Expected Outcome:
Establish a faster decision making, an intelligent medical alert system due to negligence, saving cost, better/improvise patients management and minimizing human error.
There are none real time medical data collection and if exist it will prone to human error
Expected Outcome:
Establish a faster decision making, an intelligent medical alert system due to negligence, saving cost, better/improvise patients management and minimizing human error.
Dr. Rabiah's Guest
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Project Summary
Cardiothoracic Intensive Care Units (CICU) provides continuous and often invasive measurements of hemodynamic and respiratory status in acutely ill patients with cardiac problem. Most CICU have the basic capacity to monitor and record heart rate and rhythm (usually with a built-in memory and recall capability), venous pressure, pulmonary arterial pressure, and systemic arterial pressure. The CICU medical staff must reassess these patients frequently on the basis of data from clinical observations, bedside monitors, mechanical
ventilators and a wide variety of lab tests. Clinicians usually face a very large, complex and ever-changing body of data, and it is often challenging and time consuming for them to analyze such massive information loads. Improvement in the interpretation of clinical data will have the potential of increasing quality and efficiency in the CICU.
Artificial intelligence has been recognized could be use to assist in medical clinical decision and potentially to implement automatic decision making system since mid 1950s. Intelligence can be represented or replaced by pure calculation, theoretically can simulate the thinking process of human beings. Applying artificial intelligence techniques to the medical system would be some extra concerns.
For further clarification please contact rabiah@fsktm.upm.edu.my
ventilators and a wide variety of lab tests. Clinicians usually face a very large, complex and ever-changing body of data, and it is often challenging and time consuming for them to analyze such massive information loads. Improvement in the interpretation of clinical data will have the potential of increasing quality and efficiency in the CICU.
Artificial intelligence has been recognized could be use to assist in medical clinical decision and potentially to implement automatic decision making system since mid 1950s. Intelligence can be represented or replaced by pure calculation, theoretically can simulate the thinking process of human beings. Applying artificial intelligence techniques to the medical system would be some extra concerns.
For further clarification please contact rabiah@fsktm.upm.edu.my