DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge

• URL: http://arxiv.org/abs/2405.12541v1
• Date: Tue, 21 May 2024 07:16:12 GMT
• Title: DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge
• Authors: Bufang Yang, Siyang Jiang, Lilin Xu, Kaiwei Liu, Hai Li, Guoliang Xing, Hongkai Chen, Xiaofan Jiang, Zhenyu Yan,
• Abstract summary: Large language models (LLMs) have the potential to transform digital healthcare. We introduce a novel LLM-based multi-turn virtual doctor system, DrHouse. It incorporates sensor data from smart devices in the diagnosis process, enhancing accuracy and reliability. DrHouse can achieve up to an 18.8% increase in diagnosis accuracy over the state-of-the-art baselines.
• Score: 6.975200202913554
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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. Through multi-turn interactions, DrHouse determines the next steps, such as accessing daily data from smart devices or requesting in-lab tests, and progressively refines its diagnoses. Evaluations on three public datasets and our self-collected datasets show that DrHouse can achieve up to an 18.8% increase in diagnosis accuracy over the state-of-the-art baselines. The results of a 32-participant user study show that 75% medical experts and 91.7% patients are willing to use DrHouse.

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