AGENTIC-SYSTEMSApril 15, 20261 min read13 views

A longitudinal health agent framework

Researchers propose a new multi-layer AI framework designed to support longitudinal health tasks, enabling agents to maintain coherence, adapt to evolving goals, and provide sustained support over time.

Computer Science > Artificial Intelligence

Title:A longitudinal health agent framework

View PDFAbstract:Although artificial intelligence (AI) agents are increasingly proposed to support potentially longitudinal health tasks, such as symptom management, behavior change, and patient support, most current implementations fall short of facilitating user intent and fostering accountability. This contrasts with prior work on supporting longitudinal needs, where follow-up, coherent reasoning, and sustained alignment with individuals' goals are critical for both effectiveness and safety. In this paper, we draw on established clinical and personal health informatics frameworks to define what it would mean to orchestrate longitudinal health interactions with AI agents. We propose a multi-layer framework and corresponding agent architecture that operationalizes adaptation, coherence, continuity, and agency across repeated interactions. Through representative use cases, we demonstrate how longitudinal agents can maintain meaningful engagement, adapt to evolving goals, and support safe, personalized decision-making over time. Our findings underscore both the promise and the complexity of designing systems capable of supporting health trajectories beyond isolated interactions, and we offer guidance for future research and development in multi-session, user-centered health AI.

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Source: arXiv cs.AI Recent

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