AI tools in medicine can help doctors find information quicker but might take over some of the decision-making. It's important to balance AI support and human reasoning.
AI systems often tend to agree with what users input, which can mislead doctors if they're not careful in analyzing the data. A single study might not provide the full picture.
When using AI for medical diagnosis, there's a risk that it can limit thinking to the most common conditions. Doctors need to keep an open mind about rarer possibilities.
Using LLMs can help improve how we understand what users want from an information search. This means better matching user questions to actual retrieval queries.
Having experience in a specific field helps shape these systems to give better results. It's about knowing the context in which information will be used.
By combining LLMs with domain knowledge, we can create smarter queries that fetch the right info. This makes the whole retrieval process more effective.
Providing a wider range of examples to ChatGPT helps in generating more natural-sounding outputs.
Using a local plugin for ChatGPT allows for accessing and providing context from local files for better collaboration.
Example-driven development with LLMs is useful for identifying relevant context, mimicking input characteristics, and making connections between different types of files.