mpmisko

EBMs show up all over the place, apparently even your classifier is an EBM :) (https://arxiv.org/abs/1912.03263).

GPT-based search engines usually use some sort of a database to retrieve context for the LLM to summarize first. This is what people refer to as RAG these days: https://blogs.nvidia.com/blog/what-is-retrieval-augmented-ge....

Some of these GPT engines maintain their own vector DB to do semantic search, others are directly hooked into Bing / Google. So pubmedisearch.com would be one component of a GPT-based engine. We actually have a GPT-based engine here: https://medisearch.io/.

Will definitely check pgvector, thanks for the pointer.

Lots of annoying edge cases as you can imagine, nothing particularly glamorous.

Done! Let me know if you have other feedback.

Thanks! Looks quite relevant

Training for multiple epochs is a bit like that :)

We use pinecone and it is not ideal, looking at https://turbopuffer.com/ now. They look quite promising :)

1. We cover all the articles on PMC. The exact cost is hard to estimate because we did a lot of iterations.

2. We do weight those ... it is a lot of trial and error and you have to have good & exhaustive benchmarks.

Yes

Glad you like it! I did this as a mini-project within our startup MediSearch (https://medisearch.io/) & the search pipeline is custom tuned for the problem.

Hi, it currently does not support search by PMID. But you can find the paper included in the results here (5th place):

https://pubmedisearch.com/share/Do%20some%20individuals%20wi...

Just looking at stuff like citations and impact factors of journals.

Thanks!

It uses a vector search approach. Your query is embedded in a vector space using a language model and we find the closest vector to the query from the PubMed papers. This is a good summary of the techniques: https://learn.microsoft.com/en-us/azure/search/vector-search.... There are a couple more tricks but this is the gist.

The nice part is that this approach allows you to find relevant papers to your question. E.g, you can ask "Can secondhand smoke cause AMD?" and the very first few papers are answering your question (https://pubmedisearch.com/share/Can%20secondhand%20smoke%20c...). The more specific question, the better. :)

Thanks for giving it a go! We will charge for the API and we may have a pro subscription with some nice features :).

We primarily cite medical scientific papers and health guidelines. We occasionally cite health blogs (such as healthline.com), but this is mostly for simple health questions (e.g., "tell me some nutrition tips").

Hey, a React client is definitely on our roadmap! The demo (https://tinyurl.com/medisearch-docs) in our docs is written in JS, so it should be useful out of the gate! A proper client is coming in the next few weeks.

Glad that you like it! We do support follow-up questions. Implementing a chat-style interaction should be very straightforward :) (see our Python client for examples https://pypi.org/project/medisearch-client/).