ChatGPT and other generative AI tools use probabilistic reasoning, which is a method of predicting the most likely next word or answer based on patterns in massive datasets. For example, if you say “good morning,” it knows from training data that “good morning to you too” is a likely reply. It’s powerful, but it has limitations, especially in medicine.
The problems:
- Unclear sources: You don’t know exactly where the information is coming from or its quality - social media or the New England Journal of Medicine.
- Outdated data: Training data likely does not include the latest research and is often 12 to 18 months out of date.
- Hallucinations: It can confidently make things up. Unless you know the answer, it’s hard to determine what is factually accurate.
- Limited citations: You can’t verify what’s being said or where it came from.
That’s risky, especially when health is involved.
Inciteful Med is not generative AI. It’s more like a medical librarian. We apply graph theory to the body of medical literature, while building personalized local graphs specific to your data, and applying multiple algorithms based on paper importance (using citation data) and similarity. This allows the tool to:
- Analyze your medical context
- Search peer-reviewed research for relevant passages
- Evaluate those sources for credibility and importance
- Use an LLM model to summarize what the research says
Every answer is backed by real, cited medical literature. Our database of medical literature is updated daily and includes over 40M articles from PubMed and OpenAlex. So there is never a question of quality sources, outdated data or citations.
Now, you may not always agree with what the research says, and that’s okay. But now you can bring the science into the conversation and decide what’s right for you with your doctor.
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