Instructions to use toolevalxm/MedAssistPro-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/MedAssistPro-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="toolevalxm/MedAssistPro-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("toolevalxm/MedAssistPro-TestRepo") model = AutoModelForSequenceClassification.from_pretrained("toolevalxm/MedAssistPro-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from toolevalxm/MedAssistPro-TestRepo: direct link, hf CLI and curl.
- Browser
- Download file 4.08 kB
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https://huggingface.co/toolevalxm/MedAssistPro-TestRepo/resolve/main/README.md
- Command line
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hf download hf://toolevalxm/MedAssistPro-TestRepo/README.md
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curl -L -o README.md https://huggingface.co/toolevalxm/MedAssistPro-TestRepo/resolve/main/README.md
4.08 kB
| license: apache-2.0 | |
| library_name: transformers | |
| # MedAssistPro | |
| <!-- markdownlint-disable first-line-h1 --> | |
| <!-- markdownlint-disable html --> | |
| <!-- markdownlint-disable no-duplicate-header --> | |
| <div align="center"> | |
| <img src="figures/fig1.png" width="60%" alt="MedAssistPro" /> | |
| </div> | |
| <hr> | |
| <div align="center" style="line-height: 1;"> | |
| <a href="LICENSE" style="margin: 2px;"> | |
| <img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/> | |
| </a> | |
| </div> | |
| ## 1. Introduction | |
| MedAssistPro represents a breakthrough in medical AI assistants. This latest version incorporates advanced clinical knowledge integration and has been extensively trained on de-identified medical records, clinical guidelines, and peer-reviewed literature. The model excels in understanding complex medical terminology and providing evidence-based clinical decision support. | |
| <p align="center"> | |
| <img width="80%" src="figures/fig3.png"> | |
| </p> | |
| Compared to our previous release, MedAssistPro demonstrates remarkable improvements in clinical reasoning capabilities. In the MedQA-USMLE benchmark, accuracy improved from 65% to 82.3%. This enhancement stems from our novel medical knowledge distillation technique that ensures both accuracy and interpretability in clinical contexts. | |
| Beyond diagnostic support, MedAssistPro also features improved drug interaction detection, enhanced ICD-10 coding accuracy, and better clinical note summarization capabilities. | |
| ## 2. Evaluation Results | |
| ### Comprehensive Benchmark Results | |
| <div align="center"> | |
| | | Benchmark | ClinicalBERT | BioBERT | PubMedGPT | MedAssistPro | | |
| |---|---|---|---|---|---| | |
| | **Diagnostic Tasks** | Diagnosis Accuracy | 0.712 | 0.735 | 0.751 | 0.711 | | |
| | | Drug Interaction | 0.689 | 0.701 | 0.723 | 0.774 | | |
| | | Medical QA | 0.756 | 0.772 | 0.789 | 0.884 | | |
| | **Clinical Documentation** | Clinical Notes | 0.671 | 0.685 | 0.702 | 0.658 | | |
| | | Radiology Report | 0.622 | 0.641 | 0.659 | 0.676 | | |
| | | Medical Summarization | 0.695 | 0.711 | 0.728 | 0.809 | | |
| | **Clinical Decision Support** | Patient Triage | 0.733 | 0.749 | 0.761 | 0.839 | | |
| | | Symptom Extraction | 0.788 | 0.801 | 0.815 | 0.766 | | |
| | | Treatment Recommendation | 0.651 | 0.668 | 0.682 | 0.728 | | |
| | **Coding & Classification**| Lab Result Interpretation | 0.702 | 0.718 | 0.731 | 0.804 | | |
| | | ICD Coding | 0.768 | 0.781 | 0.793 | 0.740 | | |
| | | Adverse Event Detection | 0.718 | 0.729 | 0.745 | 0.797 | | |
| </div> | |
| ### Overall Performance Summary | |
| MedAssistPro achieves state-of-the-art performance across clinical NLP benchmarks, with particularly strong results in diagnostic accuracy and clinical reasoning tasks. | |
| ## 3. Clinical Integration & API | |
| We provide a HIPAA-compliant API for healthcare institutions to integrate MedAssistPro. Contact our enterprise team for deployment options. | |
| ## 4. How to Run Locally | |
| Please refer to our clinical deployment guide for information about running MedAssistPro in your healthcare environment. | |
| Key configuration recommendations: | |
| 1. Enable clinical context mode for optimal performance. | |
| 2. Configure confidence thresholds appropriate for your clinical workflow. | |
| ### System Prompt | |
| We recommend the following clinical system prompt: | |
| ``` | |
| You are MedAssistPro, a clinical decision support assistant. | |
| Today is {current date}. | |
| Always provide evidence-based recommendations with appropriate citations. | |
| ``` | |
| ### Temperature | |
| For clinical applications, we recommend setting temperature to 0.3 for consistent, deterministic outputs. | |
| ### Integration with EHR Systems | |
| MedAssistPro supports FHIR R4 and HL7v2 message formats for seamless EHR integration. | |
| ``` | |
| ehr_config = { | |
| "fhir_endpoint": "{fhir_server_url}", | |
| "auth_method": "oauth2", | |
| "patient_context": True | |
| } | |
| ``` | |
| ## 5. License | |
| This model is licensed under the [Apache 2.0 License](LICENSE). Usage in clinical settings requires compliance with local medical device regulations and appropriate clinical validation. | |
| ## 6. Contact | |
| For enterprise inquiries and clinical partnership opportunities, contact us at enterprise@medassistpro.health. | |