Medibot AI: Synthetic Test Scenarios and Validation Artifacts (Underlying Data)

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Authors: Piero Daniel Llanos Sánchez
Cited by: 0

Abstract

This repository contains the underlying data supporting the software tool Medibot AI , a web-based intelligent system that integrates the Gemini API to generate structured informational over-the-counter (OTC) medication guidance from user-reported symptoms. To ensure transparency and reproducibility, the dataset provides a curated set of synthetic test scenarios designed to evaluate diverse symptom profiles and safety-related conditions, including pediatric cases, pregnancy, chronic diseases, and clinical red flags. All cases are fully synthetic and do not contain real patient information. Contents* Synthetic test scenarios (synthetic_test_scenarios.json): 30 structured cases (MedicalInput) representing diverse risk contexts.* Sample outputs (sample_outputs.json): example responses aligned with the Medibot AI output structure (MedicalResponse).* Schema definitions (schema.json): JSON schema describing both input and output formats. Privacy and ethics No real clinical data were collected or used. The dataset contains no patient-identifiable information and is intended exclusively for reproducibility, validation, and educational purposes. License This dataset is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Artificial Intelligence in Healthcare Innovation in Digital Healthcare Systems

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
31 January 2026
Document type
Dataset