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Product Overview
John Snow Labs produces AI and NLP models for healthcare, with use cases like healthcare-specific question answering, data de-identification, adverse drug event detection, patient risk adjustment, and clinical decision support.
Customers Served
Categories
Company Info
HQ Location
Lewes, Delaware
Founded
2015
Headcount
51-200
Total Funding
Not available
Latest Round
Not available
Latest Round
Not available
Company Socials
Anthropic
Claude AI
Company Info
Founded: 2021
Headcount: 51-200
Customers
Customers Served: Digital Health Provider, Ambulatory Practice, Hospital / Health System, Health Plan, Life Sciences, Government
Product Overview
Claude 3 is an LLM that is utilized to automate tasks like generating personalized treatment plans and summarizing medical research. It is also used to analyze large volumes of patient data, helping to create tailored healthcare solutions. The model's capabilities include supporting drug discovery, clinical research, and patient care automation.
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Meta
Llama
Company Info
Founded: 2004
Headcount: 10000+
Customers
Customers Served: Digital Health Provider, Ambulatory Practice, Hospital / Health System, Health Plan, Life Sciences
Product Overview
LLaMA 3, Meta’s latest large language model, offers significant advancements in healthcare applications. It can support a wide range of clinical tasks such as automating medical documentation, improving patient interactions, and aiding in diagnostics through natural language processing. LLaMA 3 has been integrated into tools for real-time surgical assistance, clinical trial automation, and precision medicine.
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Google
MedGemini
Company Info
Founded: 1998
Headcount: 10000+
Customers
Customers Served: Digital Health Provider, Ambulatory Practice, Hospital / Health System, Health Plan, Life Sciences
Product Overview
Security and Compliance Certifications: SOC 2 Type 2, HIPAA
Med-Gemini is an AI model family from Google, optimized for healthcare tasks like medical imaging, pathology, and genomics. It builds on Google’s Gemini models, using multimodal data and long-context reasoning to improve clinical workflows, such as generating radiology reports and predicting health outcomes from genomic data. Med-Gemini has achieved 91.1% accuracy in USMLE-style exams, and shows potential for assisting healthcare professionals in diagnostic and analytical tasks.
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