DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge
Bufang Yang, Siyang Jiang, Lilin Xu, Kaiwei Liu, Hai Li, Guoliang, Xing, Hongkai Chen, Xiaofan Jiang, Zhenyu Yan

TL;DR
DrHouse is an innovative LLM-based virtual doctor system that integrates sensor data, continuously updated medical databases, and a novel diagnostic algorithm to improve accuracy and user acceptance in digital healthcare.
Contribution
It introduces a multi-turn consultation system that combines sensor data, dynamic medical knowledge, and a new diagnostic algorithm for enhanced medical diagnosis.
Findings
Up to 18.8% increase in diagnosis accuracy over baselines
75% medical experts and 91.7% patients willing to use DrHouse
Effective multi-turn diagnostic refinement
Abstract
Large language models (LLMs) have the potential to transform digital healthcare, as evidenced by recent advances in LLM-based virtual doctors. However, current approaches rely on patient's subjective descriptions of symptoms, causing increased misdiagnosis. Recognizing the value of daily data from smart devices, we introduce a novel LLM-based multi-turn consultation virtual doctor system, DrHouse, which incorporates three significant contributions: 1) It utilizes sensor data from smart devices in the diagnosis process, enhancing accuracy and reliability. 2) DrHouse leverages continuously updating medical databases such as Up-to-Date and PubMed to ensure our model remains at diagnostic standard's forefront. 3) DrHouse introduces a novel diagnostic algorithm that concurrently evaluates potential diseases and their likelihood, facilitating more nuanced and informed medical assessments.…
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Taxonomy
TopicsSemantic Web and Ontologies
