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Medical Language Models
Python libraries and 2,000+ models for data scientists
Medical Chatbot
Get explainable answers from Healthcare-GPT on public or private data
Generative AI Lab
Train, tune, and share custom AI models without coding
Spark NLP
State-of-the-art natural language processing at scale
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Managed services
Create Patient Cohorts
Use Medical Generative AI to Answer Patient Questions from Raw Clinical Data
De-Identification
Anonymize and obfuscate structured, free text, and imaging data with over 99% accuracy
Patient Risk Adjustment
Automate patient risk adjustment and HCC Coding from clinical notes
Regulatory-Grade Data Abstraction
Automatic & faster data abstraction, with a human in the loop
TURNKEY SOLUTIONS
Responsible AI with LangTest
Deliver safe and effective language models, by generating and running 100+ test types
Medical Knowledge Graphs
Build a longitudinal view of the patient, connecting noisy & diverse data sources
Adverse Drug Event Detection
Detect adverse drug events from unstructured clinical records, transcripts, and messages
Clinical Decision Support
Predict patient risk based on a holistic view of the entire medical record
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The Power of Small LLMs in Healthcare: A RAG Framework Alternative to Large…
From Data Overload to Precision: How Medical Language Models Enhance Clinic…
Harnessing Healthcare-Specific LLMs for Clinical Entity Extraction
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November 13
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De-Identification of Medical Images in DICOM Format
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The Power of Small LLMs in Healthcare: A RAG Framework Alternative to Large Language Models
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Bugra Ekinci
In this blog post, we spotlight the potential of smaller, specialized language models within a Retrieval-Augmented Generation (RAG) framework — a space where large LLMs like GPT-4o are commonly used. By examining JSL’s purpose-built...