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A ReAct Agentic AI System for Natural Language Querying and Statistical Analysis of The Cancer Genome Atlas Clinical Data

2026-07-17

Abstract excerpt

The Cancer Genome Atlas (TCGA) holds clinical data for over 11,000 patients across 33 cancer types, but access is hard because of complex file structures, heterogeneous formats, and the need for programming. We present an agentic system for natural language querying and statistical analysis of TCGA clinical data. The system uses a large language model as an autonomous ReAct agent that selects from eight computatio...

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Literature Corpus work
28a84a56-4d6c-560d-82ef-81581b0f6b78
DOI
10.64898/2026.07.15.26358188
Open publication

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A ReAct Agentic AI System for Natural Language Querying and Statistical Analysis of The Cancer Genome Atlas Clinical DataDOI 10.64898/2026.07.15.26358188
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