John Snow Labs, the AI for healthcare company, has won the 2024 Global 100 Award for the Best Medical Application of Large Language Models (LLMs). The award recognizes not only the company’s product innovation, but also its established customer success. Several such case studies were presented by the US Veteran’s Administration, ClosedLoop, and WiseCube at John Snow Labs’ annual Natural Language Processing (NLP) Summit, now the world’s largest gathering of applied NLP and LLM practitioners.
John Snow Labs is leading efforts in responsible AI for healthcare through the development of the open-source LangTest library, which now supports over 100 test types of benchmarks that can automatically evaluate LLMs. In addition, the team is part of the Coalition for Health AI (CHAI), a nonprofit that comprises health systems, technology companies, civil and government organizations, and expert AI practitioners, created to provide a framework for healthcare AI tools. John Snow Labs’ CTO, David Talby, is the co-lead of the fairness, equity, and bias mitigation workgroup at CHAI.
The company’s newly released Medical Chatbot provides a conversational interface to a suite of medical knowledge bases, updated daily. The Medical Chatbot is designed to help experts stay current with medical research, case reports, trials, terminologies, and their organization’s private content, all using a simple natural language interface. The chatbot provides full explainability by always citing its sources, and prioritizes privacy through features like role-based access.
Additionally, John Snow Labs has developed a series of new integrations with partners to enable customers to build end-to-end solutions faster. For example, longtime partner Databricks leveraged the company’s healthcare-specific models to build a Retrieval Augmented Generation (RAG) LLM clinical chatbot. John Snow Labs now has 26 partners including Oracle, AWS, Azure, Deloitte, CarahSoft, Accenture, and Booz Allen Hamilton.
“Generative AI and LLMs took 2023 by storm, but delivering enterprise-grade systems that are accurate, responsible, and scalable is not yet a reality for most organizations,” said David Talby. “We’re taking medical LLMs beyond the hype, productizing the latest AI research to advance the state-of-the-art and help the healthcare industry put it to good use faster.”