An expert system for selecting wart treatment method.

Area of Science:

• Dermatology
• Medical Informatics
• Computational Biology

Background:

• Warts, benign skin tumors caused by Human Papillomavirus (HPV), affect various body parts, particularly hands and feet.
• Current treatments for warts lack universal efficacy, necessitating research into more effective and personalized therapeutic approaches.
• Physicians seek methods to predict treatment responses for individual patients to optimize wart management.

Purpose of the Study:

• To identify optimal treatments for common and plantar warts.
• To predict the treatment responses of immunotherapy and cryotherapy using a fuzzy logic system.
• To enhance personalized medicine in dermatology for HPV-related conditions.

Main Methods:

• A study involving 180 patients with common or plantar warts at Ghaem Hospital, Mashhad, Iran.
• Randomized treatment allocation: 90 patients received cryotherapy (liquid nitrogen), and 90 received immunotherapy.
• Development and implementation of a fuzzy logic rule-based system for predicting treatment outcomes.

Main Results:

• The fuzzy logic system demonstrated a prediction accuracy of 83.33% for immunotherapy.
• Cryotherapy prediction accuracy was observed to be 80.7%.
• The developed expert system shows potential for improving treatment selection and patient outcomes.

Conclusions:

• The fuzzy logic system effectively predicts patient response to immunotherapy and cryotherapy for warts.
• This approach can assist clinicians in choosing the most suitable treatment, potentially reducing costs and improving care quality.
• Personalized treatment prediction systems offer significant benefits for managing common dermatological conditions like warts.