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Data · dataset · 2026

A Pediatric Consultation Dialogue Dataset with Pediatrician-Validated Reasoning Annotations

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This bilingual pediatric consultation dialogue dataset, featuring expert-validated annotations of clinical reasoning, was developed to facilitate research on pediatric medical dialogue systems, clinical reasoning processes, and large language models.

Description

The data were derived from authentic text-based telemedicine consultations for pediatric patients, conducted via the Internet Hospital of the Children's Hospital of Chongqing Medical University (CHCMU) over the period from January 2020 to June 2023.Dataset construction included dialogue sampling, eligibility screening, de-identification, reasoning annotation, bilingual translation, expert review, and data validation.

Personal identifiers were removed through a multi-stage de-identification process combining automated processing with manual verification. For each physician response, an initial reasoning annotation was generated by a large language model and subsequently reviewed and corrected by pediatricians. English translations were also verified against the original Chinese dialogues.The released dataset contains 947 pediatric consultation dialogues comprising more than 10,000 dialogue turns.

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Each physician turn is paired with one expert-reviewed reasoning annotation. The dataset is provided in JSONL format together with metadata and predefined training, validation, and test splits for downstream machine learning research. Some demographic or clinical variables may be unavailable when they were not recorded during the original consultation; these missing values reflect the source records rather than processing errors.

The dataset is intended for research purposes only. All preprocessing scripts and downstream fine-tuning examples are available in the accompanying code repository.

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Provenance · 1 source records, 12 field assertions
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