MediTOD: An English Dialogue Dataset for Medical History Taking with Comprehensive Annotations

TL;DR

MediTOD is a comprehensive English medical dialogue dataset with detailed annotations, designed to improve medical history-taking systems and facilitate research in dialogue understanding, policy learning, and generation.

Contribution

The paper introduces MediTOD, a new annotated dataset for medical dialogues, addressing privacy issues and lack of detailed annotations in existing datasets.

Findings

Established benchmarks for NLU, policy, and NLG tasks.

Demonstrated effectiveness of models on MediTOD in supervised and few-shot settings.

Provided publicly available dataset for future research.

Abstract

Medical task-oriented dialogue systems can assist doctors by collecting patient medical history, aiding in diagnosis, or guiding treatment selection, thereby reducing doctor burnout and expanding access to medical services. However, doctor-patient dialogue datasets are not readily available, primarily due to privacy regulations. Moreover, existing datasets lack comprehensive annotations involving medical slots and their different attributes, such as symptoms and their onset, progression, and severity. These comprehensive annotations are crucial for accurate diagnosis. Finally, most existing datasets are non-English, limiting their utility for the larger research community. In response, we introduce MediTOD, a new dataset of doctor-patient dialogues in English for the medical history-taking task. Collaborating with doctors, we devise a questionnaire-based labeling scheme tailored to the medical domain. Then, medical professionals create the dataset with high-quality comprehensive annotations, capturing medical slots and their attributes. We establish benchmarks in supervised and few-shot settings on MediTOD for natural language understanding, policy learning, and natural language generation subtasks, evaluating models from both TOD and biomedical domains. We make MediTOD publicly available for future research.