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# π₯ AI Diagnostics Agent: Early Cancer Discovery
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AI-powered demo for early cancer risk detection using chest X-rays, lab markers, and explainable summaries.
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β οΈ
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## What it does
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This project demonstrates a multi-agent AI approach for early cancer risk detection:
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- **Imaging Agent** πΌοΈ: Analyzes chest X-rays for findings relevant to lung cancer (*Mass, Nodule, Lung Opacity*).
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- Produces probability scores.
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- Display an optional **heatmap overlay** showing suspicious regions.
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- **Lab Agent** π§ͺ: Parses tumor marker labs (PSA, CA125, AFP) from text and flags elevated results.
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- **Coordinator Agent** π: Combines imaging + lab results into an early cancer screening summary with disclaimers.
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- **Extra Samples**: MRI and CT text reports are included as input examples for future expansion.
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##
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- `samples/sample_xray2.png` β suspicious chest X-ray
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- `samples/sample_labs.txt` β tumor marker results
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- `samples/sample_mri.txt` β example MRI report
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- `samples/sample_ct.txt` β example CT scan report
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# π₯ AI Diagnostics Agent: Early Cancer Discovery (Demo)
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**β οΈ Research demo only β not for clinical use**
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### π Overview
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AI Diagnostics Agent is a **proof-of-concept early cancer screening tool** combining:
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- **Imaging Agent** β analyzes chest X-rays using TorchXRayVision to detect lung anomalies (mass, nodule, opacity) and generate heatmaps.
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- **Lab Agent** β parses tumor marker results (PSA, CA125, AFP) for abnormal readings.
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- **AI Coordinator (Moonshot.ai)** β uses a large language model to summarize overall cancer risk, highlight abnormalities, and suggest next steps in human-readable form.
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### π§ Powered by Moonshot.ai
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The AI Coordinator uses [Moonshot.ai](https://www.moonshot.cn) LLM API to generate intelligent summaries.
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