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# 🧠Clinical Reasoning AI – Kenya Challenge 2024
This project was developed as part of the **Kenya Clinical Reasoning AI Challenge 2024**, a collaborative initiative aimed at improving healthcare decision-making through artificial intelligence. It focuses on building and evaluating AI models that assist medical professionals with **clinical diagnosis, triage, and patient reasoning** — particularly in **low-resource settings**.
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## 🌍 Context
In many African countries, especially in rural regions, access to experienced clinicians is limited. This challenge aimed to explore how **Large Language Models (LLMs)** and **clinical AI systems** could support junior healthcare workers or community health workers by providing intelligent reasoning support.
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## 🎯 Project Goals
- Build an **LLM-powered assistant** to interpret patient symptoms and medical notes
- Use **clinical case data** from Kenyan health institutions
- Evaluate diagnostic reasoning with **F1-score, confidence calibration, and safety thresholds**
- Provide **explainable outputs** for physician trust and oversight
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## đź’ˇ Key Features
- đź§ Fine-tuned LLM for clinical reasoning tasks
- đź“‹ Ingests case data and outputs probable diagnoses
- đź’¬ Generates natural-language reasoning chains ("why" behind diagnosis)
- 📉 Scores confidence and suggests referral when uncertain
- 🛡️ Includes safety thresholds to prevent overconfidence
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## đź§Ş Example Input
```plaintext
Patient: 8-year-old female, fever for 3 days, vomiting, headache, no neck stiffness, no rash.