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Managing urinary incontinence through hand-held real-time decision support aid
Constantinos Koutsojannis1, Chrysa Lithari, Ioannis Hatzilygeroudis
1Technological Educational Institute of Patras, Physiotherapy Department, Psaron 6, 25100 Aigion, Greece. ckoutsog@teipat.gr
Computer Methods and Programs in Biomedicine
|March 31, 2012
Summary
An intelligent system, e-URIN, aids in diagnosing and treating urinary incontinence (UI) in both males and females. This decision support tool, accessible via e-health, shows promising initial results for clinical use.
Area of Science:
- Urology
- Medical Informatics
- Artificial Intelligence in Healthcare
Background:
- Urinary incontinence (UI) affects both males and females, necessitating accurate diagnosis and effective treatment strategies.
- Existing diagnostic and treatment methods can be complex, highlighting the need for advanced decision support systems.
- The integration of e-health tools and intelligent systems offers potential to improve patient care and medical education.
Purpose of the Study:
- To introduce e-URIN, an intelligent system for the diagnosis and treatment of urinary incontinence.
- To develop a user-friendly, accessible decision support system for healthcare professionals and an educational tool for medical students.
- To leverage expert knowledge and clinical data for improved UI management.
Main Methods:
- Development of an expert system incorporating urology expert knowledge.
- Integration of bibliographic search and statistical analysis of clinical practice data.
- Implementation on a hospital server supporting e-health tools and wireless connectivity for pocket PCs.
Main Results:
- Preliminary experimental results on a real patient hospital database demonstrate acceptable performance.
- The e-URIN system functions as a decision support tool for resident doctors.
- The system also serves as an educational resource for medical students.
Conclusions:
- The e-URIN system shows potential for effective diagnosis and treatment of urinary incontinence.
- Further improvements in performance are anticipated with the integration of additional computational intelligence approaches.
- The system's design supports accessibility and usability in clinical and educational settings.
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