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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.15321393 |
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Table of Contents:
- <p><span>ChatAlchemy is an AI-powered conversational platform developed to streamline and enhance the process of biomedical research. It enables users to engage with both structured datasets and unstructured scientific literature through natural language interactions. At its core, the system integrates a large language model (GPT-4 Turbo) with a vector database constructed from the PharmAlchemy dataset to enable semantic search and contextual retrieval. This architecture allows researchers to perform general biomedical queries, targeted data exploration, and literature-based discovery without the need for programming expertise. The platform also supports the automated analysis of uploaded documents, identifying key biomedical entities such as genes, diseases, and drugs. These entities are then contextualized and presented using intuitive visual interfaces, enabling users to uncover complex relationships and patterns. ChatAlchemy addresses the growing demand for accessible, intelligent research tools by unifying conversational AI, semantic retrieval, and document analysis into a cohesive system. This report presents the motivation, design, implementation, and evaluation of ChatAlchemy, along with a representative case study and a discussion on its potential applications and future development.</span></p>