Paper Detail
Abdulkadir Külçe, Alihan Esen, Cağla Fikir, Berke Kurt, Kuzey Arar, Gökhan Ercan, Faik Boray Tek
This paper presents ECHO (Enhanced Care \& Health Observer), a locally-deployable conversational health assistant for long-term chronic care management. ECHO integrates three complementary software modules developed under shared supervision as a unified system. The core module is an agentic chatbot built on a ReAct loop orchestrated via LangGraph, equipped with 17 clinical tools and a temporal knowledge graph for persistent cross-session memory; it achieves a 94.9\% tool-execution pass rate across a 59-scenario benchmark with GPT-5 Mini. A two-stage hybrid safety layer intercepts all incoming queries: a rule-based layer handles explicit crisis signals and jailbreak attempts in under 1ms, while a signed graph neural network (GNN) with APPNP-style propagation classifies boundary cases by clinical intent, achieving 88.8\% accuracy and 90.6\% unsafe recall on a 2,537-query annotated Turkish health dataset while outperforming zero-shot LLM baselines including Llama 3.3 70B. A multimodal speech assessment module combining Whisper acoustic encoding and BERT text encoding with cross-attention fusion estimates emotion, depression, and pain, reaching a mean macro F1 of 0.652. The full system is implemented as a web application that can run entirely on consumer hardware, with no patient data transmitted to external services, supporting compliance with GDPR and KVKK.
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@article{kle2026echo,
title = {ECHO: A Locally-Deployable Agentic Health Assistant with Temporal Memory, Safety Guardrails, and Speech Assessment},
author = {Abdulkadir Külçe and Alihan Esen and Cağla Fikir and Berke Kurt and Kuzey Arar and Gökhan Ercan and Faik Boray Tek},
year = {2026},
abstract = {This paper presents ECHO (Enhanced Care \textbackslash{}\& Health Observer), a locally-deployable conversational health assistant for long-term chronic care management. ECHO integrates three complementary software modules developed under shared supervision as a unified system. The core module is an agentic chatbot built on a ReAct loop orchestrated via LangGraph, equipped with 17 clinical tools and a temporal knowledge graph for persistent cross-session memory; it achieves a 94.9\textbackslash{}\% tool-execution pass rate acro},
url = {https://arxiv.org/abs/2608.06110},
keywords = {cs.AI, cs.CL},
eprint = {2608.06110},
archiveprefix = {arXiv},
}
{}