Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-fai Wong, Xiangying Dai
| Challenge: | Existing methods to identify phenotypes using electronic health records (EHRs) are expensive and difficult to transfer models from one disease to another. |
| Approach: | They propose a task-oriented dialogue system framework to make diagnosis for patients automatically, which can converse with patients to collect additional symptoms beyond their self-reports. |
| Outcome: | The proposed system can collect additional symptoms from conversation and improve disease identification accuracy. |
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| Challenge: | Task-oriented dialogue systems have been surveyed in the medical community from a non-technical perspective, but a systematic review from . a rigorous computational perspective has to date remained noticeably absent. |
| Approach: | They analyze 4070 papers on task-oriented dialogue systems for healthcare applications and identify gaps in their analysis. |
| Outcome: | The proposed system-level implementation details remain limited or underspecified, slowing the pace of innovation in this area. |
D4: a Chinese Dialogue Dataset for Depression-Diagnosis-Oriented Chat (2022.emnlp-main)
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| Challenge: | Existing human-machine dialogue systems are not able to provide diagnostic information for depression diagnosis due to stigma associated with mental illness. |
| Approach: | They propose to construct a Chinese Dialogue Dataset for depression-diagnosis-oriented chat based on clinical depression diagnostic criteria. |
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Reasoning Like a Doctor: Improving Medical Dialogue Systems via Diagnostic Reasoning Process Alignment (2024.findings-acl)
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| Challenge: | Medical dialogue systems have attracted significant attention for their potential to act as medical assistants. |
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Extracting relevant information from physician-patient dialogues for automated clinical note taking (D19-62)
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| Challenge: | a system that extracts pertinent medical information from dialogues between clinicians and patients is proposed . entering data into EMRs is currently slow and error-prone, and clinicians spend up to 50% of their time on data entry. |
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Enhancing Dialogue Symptom Diagnosis with Global Attention and Symptom Graph (D19-1)
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| Challenge: | Existing studies on symptom diagnosis based on EHRs focus on the standard electronic medical records, but the dialogues between doctors and patients that contain more rich information are not well studied. |
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MediTOD: An English Dialogue Dataset for Medical History Taking with Comprehensive Annotations (2024.emnlp-main)
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| Challenge: | Existing datasets lacking comprehensive annotations for medical history-taking are non-English . existing datasets lack comprehensive annotation for medical slots and their attributes . |
| Approach: | They propose a dataset of doctor-patient dialogues in English for medical history-taking task. |
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DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction (2025.findings-acl)
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| Challenge: | Existing medical LLMs focus primarily on diagnosis recommendation, limiting their clinical applicability. |
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ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems (2020.acl-demos)
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Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang
| Challenge: | ConvLab-2 inherits Convlab's framework but integrates more powerful dialogue models and supports more datasets. |
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CoAD: Automatic Diagnosis through Symptom and Disease Collaborative Generation (2023.acl-long)
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| Challenge: | Automated diagnosis (AD) is a critical application of AI in healthcare . despite its simplicity and superior performance, a decline in disease diagnosis accuracy is observed . |
| Approach: | They propose a new collaborative disease and symptom generation framework to improve automatic diagnosis. |
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A Virtual Patient Dialogue System Based on Question-Answering on Clinical Records (2024.lrec-main)
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| Challenge: | a new approach to annotating medical dialogues with intents is proposed for virtual patients . a VP is a system that allows medical students to simulate a real clinical consultation . |
| Approach: | They propose to annotate medical dialogue questions in Spanish and a second dataset of dialogues using a novel annotation approach. |
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