A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Patient-Reported Outcomes

Background:

• Active patient documentation enhances understanding of therapy efficacy, disease progression, and quality of life in chronic conditions like hematologic malignancies.
• Artificial intelligence (AI), including natural language processing (NLP) and speech recognition, has enabled new healthcare tools.
• Existing tools often lack language-specific adaptations for diverse patient populations.

Purpose of the Study:

• To introduce an innovative, Greek-language conversational agent designed for patients with hematologic malignancies.
• To utilize AI, specifically sentiment analysis, for collecting detailed family histories and symptom data.
• To assess the feasibility and user experience of this novel healthcare tool.

Main Methods:

• Development of a conversational agent with NLP and sentiment analysis capabilities.
• Tailoring the agent for the Greek language and specific needs of hematologic malignancy patients.
• Conducting a feasibility study to evaluate the tool's effectiveness and user reception.

Main Results:

• The conversational agent successfully incorporates sentiment analysis for data collection.
• Preliminary feasibility study findings indicate positive user experience and usability.
• The tool demonstrates potential for enhanced patient engagement in clinical settings.

Conclusions:

• The Greek-language conversational agent is a promising tool for collecting patient-reported data in hematologic malignancies.
• AI-driven conversational agents can improve the efficiency and depth of patient data gathering.
• Further research should explore the long-term impact on patient outcomes and clinical decision-making.