Dataset for Interpretable Medical Diagnosis Using BERT with Chain of Thought and Explainable AI
Year: 2025
Type: article
Abstract: This dataset supports the study titled "Integrating Chain of Thought and Explainable AI in BERT-Based Deep Learning for Interpretable Medical Diagnosis". It consists of anonymized textual clinical records used to train and evaluate a BERT-based classification model enhanced with Chain of Thought (CoT) reasoning and Explainable AI (XAI) techniques. The data includes patient complaint narratives and corresponding diagnostic labels, formatted to facilitate both semantic understanding and structured reasoning steps. This resource is intended for researchers working on natural language processing in healthcare, particularly those focused on interpretability and trust in AI-based decision support systems. The dataset was utilized in the model development and performance analysis presented in the related publication.
Authors: Binsar, Faisal, sasmoko
Institutions: Binus University, Universitas Muhammadiyah Berau
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6949665825
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