Patient decision support system and operating method based on self-care algorithms that evaluate patient activity for patients diagnosed with liver cirrhosis

The patient decision support system addresses the lack of comprehensive content in existing systems by using self-care algorithms for real-time feedback and symptom assessment, enhancing patient engagement and remote monitoring for effective liver cirrhosis management.

WO2026147463A1 Publication Date: 2026-07-09AKDENIZ UNIVERSITESI DONER SERMAYE ISLETME MUDURLUGU
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Patent Information

Application Number
PCT/TR2025/051942
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Filing Date
2025-12-29
Publication Date
2026-07-09

AI Technical Summary

Technical Problem

Existing patient decision support systems for liver cirrhosis lack comprehensive educational content, fail to enhance patient participation in self-care practices, and lack real-time feedback and symptom assessment, making them inadequate for effective remote monitoring and management of the disease.

Method used

A patient decision support system utilizing self-care algorithms that evaluate patient activity through artificial intelligence, providing personalized recommendations, real-time feedback, and symptom assessment, integrated with telehealth platforms to encourage active participation in daily health practices.

Benefits of technology

Enhances patient engagement in self-care, enables continuous remote monitoring, and early detection of complications, improving treatment adherence and quality of life for patients with liver cirrhosis.

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Abstract

The invention relates to a patient decision support system and operating method based on self-care algorithms that evaluate patient activity for patients diagnosed with liver cirrhosis, which is intended to monitor and manage patients' health conditions, provides regular data tracking and personalised recommendations, tracks patients' daily and weekly activities, medication use, diet, and exercise routines, collects and evaluates the data, and presents user-specific recommendations, and which uses artificial intelligence and care algorithms to determine, on the basis of the patient's health data, which treatment and care pathways are the most appropriate.
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