This repository explores training a ChatGPT-like model for primary care medicine, aiming to efficiently collect patient histories and generate differential diagnoses. It targets medical professionals and researchers interested in AI-assisted healthcare. The project's primary benefit is to streamline clinical workflows and potentially improve diagnostic accuracy.

How It Works

The project investigates fine-tuning large language models (LLMs) on medical data. The core approach involves adapting existing LLM architectures, like ChatGPT, to the specific domain of primary care. The goal is to imbue the model with the ability to understand and process complex medical information, leading to more accurate patient history collection and differential diagnosis generation.

Highlighted Details

• Explores fine-tuning LLMs for medical applications.
• Aims for efficient patient history collection.
• Focuses on generating differential diagnoses.
• References research on LLMs in medicine and their capabilities.

Maintenance & Community

This appears to be a personal exploration project with no explicit mention of a community, ongoing maintenance, or notable contributors.

Licensing & Compatibility

The README does not specify a license. The project's nature, involving potential fine-tuning on medical data, may have licensing and privacy implications not detailed here.

Limitations & Caveats

The author expresses doubt about the project's current feasibility for comprehensive assessment and planning, suggesting utility primarily for scribing basic cases. The potential for fine-tuning on proprietary medical databases like Up-To-Date is mentioned but also questioned.