
MediSearch
Get an instant answer to your medical questions
What it does
MediSearch is a search engine that provides direct answers to health questions based on trustworthy sources. We want to enable people to find accurate answers for any medical question within seconds.
Does a similar job
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- SESearch engine for trustworthy medical information2023 · medisearch.io · ▲5
Hi HN, I’d like to share MediSearch with you. A few months ago, I had a knee injury and got several surgery options from doctors. I had to make an important decision, but the medical information search experience was terrible. The sites I found either did not answer my questions (long health blogs) or were too technical to easily understand (scientific papers). This gave me and my friend the idea for MediSearch. Our goal is to build a system that provides direct accurate answers to medical questions based on trustworthy sources. We’d like to make MediSearch helpful to everyone and we still…
- MLMedical LLM API on par with Google Med-PaLM 2. 92% USMLE accuracy2023 · medisearch.io · ▲17
Hello HN! I’d like to share a medical question-answering API which has state-of-the-art performance on the USMLE self-assessment exam. You can try out the MediSearch API in 10 seconds in this Colab [https://tinyurl.com/medisearch-colab], or test the search engine live at MediSearch [https://medisearch.io]. See our API page [https://medisearch.io/api] to apply for access. Some technical highlights: 1. State-of-the-art accuracy of 92% on the USMLE self-assessment exam [https://tinyurl.com/medisearch-eval]. 2. Ranked 2nd on MedQA benchmark,…


- IPI put PubMed in a vector DB2024 · pubmedisearch.com · ▲97
Hi HN, As a researcher, I often found myself struggling with the limitations of keyword-based search when exploring PubMed papers. To address this, I created PubMed Search (https://www.pubmedisearch.com/), a tool that leverages a vector database to enable semantic search across medical research literature. Some key features: * Daily updates to ensure access to the latest articles * Semantic search using latest & greatest embedding models * Some additional useful info about the papers (tldr, journal, publication date, etc.) Hope you find it useful!
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Source: Product Hunt launch ↗
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