The dataset contains real-world clinical vignettes drawn from frontline healthcare settings across Kenya. Each sample presents a prompt representing a clinical case scenario, along with the response from a human clinician. Your goal is to predict the clinician's response based on the prompt.

These vignettes simulate the types of decisions nurses in Kenya must make every day, particularly in low-resource environments where access to specialists or diagnostic equipment may be limited.

Each prompt was originally answered by expert clinicians as well as multiple large language models (LLMs) as part of a research initiative on AI in healthcare. For this challenge, we focus only on replicating the human clinician response.

Important Notes

• These are real clinical scenarios, and the dataset is small because expert-labelled data is difficult and time-consuming to collect.
• Prompts are diverse across medical specialties, geographic regions, and healthcare facility levels, requiring broad clinical reasoning and adaptability.
• Responses may include abbreviations, structured reasoning (e.g. "Summary:", "Diagnosis:", "Plan:"), or free text.