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State-of-the-art Accuracy models
Access to state-of-the-art accuracy models designed specifically for the healthcare domain. Supported tasks include summarization, question answering, entity recognition for 400+ entity types, assertion status detection (identify between positive, negative, possible, past, and future facts), clinical relation extraction, clinical entity resolution to SNOMED-CT, ICD-10, CPT, RxNorm, LOINC, NDC, ICD-I, MeSH, UMLS.
Visual Document Understanding
Support for Visual Document Understanding. Access to software and models that enable form understanding, table detection and extraction, noisy image enhancement, visual document classification, visual entity recognition, signature detection, and image de-identification.
Developer resources
John Snow Labs Medical LLM
Explore Medical LLM - Medical Large Language Models Demos & Notebooks.
Related resources
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Accelerate Product Development and Market Launch
John Snow Labs Medical LLM is built for summarization of clinical notes and is preferred 88% more often on factuality, 92% more often on relevance, 68% more often on conciseness compared to GPT-4o. Sample Questions: Summarize the final pathological diagnosis of the lesion and the patient’s follow-up and recovery after surgery. Summarize the patient’s medical history and initial presentation. Summarize the background and objectives of the study from the given text.
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Clinical Information Extraction
John Snow Labs Healthcare NLP portfolio consists of the largest healthcare pre-trained models for clinical data curation. One license gives you access to 400+ entity types, assertion status detection (identify between positive, negative, possible, past, and future facts), clinical relation extraction, clinical entity resolution to SNOMED-CT, ICD-10, CPT, RxNorm, LOINC, NDC, ICD-I, MeSH, UMLS.
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Biomedical Question Answering
John Snow Labs Medical Reasoning LLM is preferred 175% more often on factuality, 200% more often on relevance, 256% more often on conciseness compared to GPT-4o. Sample Questions: Given the report, what biomarkers are commonly negative in APL cases? Given the note, why is the chemotherapy the mainly used treatment in TNBC patients? Given the article, what is sNFL used for?
Your account is almost complete! To quickly access your account, Q: What is the pricing model?
A: Our software is an annual subscription model with access to over 2700+ pre-trained medical language models accessible and downloadable with a license key. The annual subscription provides all the updates and improvements.
Q: Can I run your models on patient data?
A: Yes, our models can run in HIPAA compliant environment or airgap environment on patient data.
Q: What can I use this API for?
A: The API supports diverse healthcare workflows including clinical data integration, AI model training, population health analytics, care coordination, quality reporting, and regulatory compliance. It's particularly valuable for EMR integrations, health information exchanges, clinical decision support systems, and AI agent implementations requiring standardized data inputs.
Q: Can I tune your models?
A: Yes, not only can you tune our models in your environment on your own data, but the improved models also you tuned are only used by you. John Snow Labs does not have access to your data, and the models are never trained on customer data.
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