/* # Copyright 2025 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. */ import React from 'react'; import styles from './DetailsOverlay.module.css'; import IconClose from '../icons/IconClose'; const DetailsOverlay = ({onClose}) => { return (
e.stopPropagation()}>

Details About This Demo

The Model: This demo features Google's MedGemma-27B, a Gemma 3-based model fine-tuned for comprehending medical text and images, specifically Chest X-Rays. It demonstrates MedGemma's ability to facilitate the learning process for medical students by advanced interpretation of medical images and contextual question generation while leveraging clinical guidelines. Context from clinical guidelines are generated using RAG which utilizes Google's MedSigLIP embedding model to build a vector index database.

Accessing and Using the Model: Google's MedGemma-27B is available on{' '} HuggingFaceHugging Face Logo {' '} and{' '} Model Garden Model Garden Logo . Learn more about using the model and its limitations on the{' '} HAI-DEF developer site .

Health AI Developer Foundations (HAI-DEF): Provides a collection of open-weight models and companion resources to empower developers in building AI models for healthcare.

Enjoying the Demo? We'd love your feedback! If you found this demo helpful, please show your appreciation by clicking the ❤️ button on the HuggingFace page, linked at the top.

Explore More Demos: Discover additional demos on HuggingFace Spaces or via Colabs:

  • CXR Foundations Demo Hugging Face Logo {' '} - Showcases on-browser, data-efficient, and zero-shot classification of CXR images.
  • Path Foundations Demo Hugging Face Logo {' '} - Highlights on-browser, data-efficient classification and outlier detection within pathology slides.
  • MedGemma Rad Explain Link icon {' '} - Analyzes a radiology report and its corresponding CXR/CT image, generating AI explanations for selected sentences with visual context.
  • Finetune MedGemma Colab Google Colab Logo {' '} - See an example of how to fine-tune this model.
  • Simulated Pre-visit Intake Link icon {' '} - Simulates a pre-visit patient dialogue, generating an intelligent intake report with self-evaluated insights for efficient provider use.
); }; export default DetailsOverlay;