Using GPT-3 and Whisper to save doctors’ time
Hey HN, We're Alex, Martin and Laurent. We previously founded Wit.ai (W14), which we sold to Facebook in 2015. Since 2019, we've been working on Nabla (https://nabla.com), an intelligent assistant for health practitioners. When GPT-3 was released in 2020, we investigated it's usage in a medical context[0], to mixed results. Since then we’ve kept exploring opportunities at the intersection of healthcare and AI, and noticed that doctors spend am awful lot of time on medical documentation (writing clinical notes, updating their EHR, etc.). Today, we're releasing Nabla Copilot, a…
In plain words
Nabla Copilot is a Chrome extension that automatically generates clinical notes from video consultations between doctors and patients. Using GPT-3 and Whisper technology, it transcribes and summarizes patient interactions, reducing the time healthcare practitioners spend on medical documentation and electronic health record updates. The tool is designed for doctors and medical professionals seeking to streamline administrative tasks during their practice.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN, We're Alex, Martin and Laurent. We previously founded Wit.ai (W14), which we sold to Facebook in 2015. Since 2019, we've been working on Nabla (https://nabla.com), an intelligent assistant for health practitioners. When GPT-3 was released in 2020, we investigated it's usage in a medical context[0], to mixed results. Since then we’ve kept exploring opportunities at the intersection of healthcare and AI, and noticed that doctors spend am awful lot of time on medical documentation (writing clinical notes, updating their EHR, etc.). Today, we're releasing Nabla Copilot, a Chrome extension generating clinical notes from video consultations, to address this problem. You can try it out, without installation nor sign up, on our demo page: https://nabla.com/copilot-demo/ Here’s how it works under the hood: - When a doctor starts a video consultation, our Chrome extension auto-starts itself and listens to the active tab as well as the doctor’s microphone. - We then transcribe the consultation using a fine-tuned version of Whisper. We've trained Whisper with tens of thousands of hours of medical consultation and medical terms recordings, and we have now reached an error rate which is 3× lower than Google's Speech-To-Text. - Once we have the transcript, we feed it to a heavily trained GPT-3, which generates a clinical note. - We finally return the clinical note to the doctor through our Chrome extension, the doctor can copy it to their EHR, and send a version to the patient. This allows doctors to be fully focused on their consultation, and saves them a lot time. Next, we want to make this work for in-person consultation. We also want to extract structured data (in the FHIR standard) from the clinical note, and feed it to the doctor’s EHR so that it is automatically added to the patient's record. Happy to further discuss technical details in comments! --- [0]: https://nabla.com/blog/gpt-3/
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, March 2023
the whole month →
- BI
I'm a big fan of the BBC podcast In Our Time -- and (like most people) I've been playing with the OpenAI APIs. In Our Time has almost 1,000 episodes on everything from Cleopatra to the evolution of teeth to plasma physics, all still available, so it's my starting point to learn about most topics. But it's not well organised. So here are the episodes sorted by library code. It's fun to explore. Web scraping is usually pretty tedious, but I found that I could send the minimised HTML to GPT-3 and get (almost) perfect JSON back: the prompt includes the Typescript definition. At the same time I…
AI · 2023 · genmon.github.io