John Snow Labs’ Post

📣 Be part of the largest global community in Applied NLP, LLM, and Generative AI at the 2024 NLP Summit! 🌍🤝 📅 Dates: September 24-26 🧐 Expectations: - A rich three-day program featuring over 50 technical discussions. - Specialized focus days dedicated to open source, healthcare, and practical applications. • Interactive Q&A sessions with industry experts. - Opportunities for networking with peers. - Post-event on-demand access to all presentations. 🌟 Following the main event, join us for a week of live training workshops ranging from beginner to advanced levels, complete with certifications. Engage, exchange, and discover effective AI utilization practices! Secure your spot today: https://hubs.li/Q02CWMp30 #GenerativeAI #HealthcareAI #MedicalLLMs #nlp #naturallanguageprocessing #DataScience #DataEngineering #DataAnalysis #DataInsights #TextProcessing #DeepLearning #DataScience

Articulate Medical Intelligence Explorer (AMIE) is a research #AI system based on an LLM that is optimized for diagnostic reasoning and conversations. Michael’s team trained and evaluated AMIE along many dimensions that reflect quality in real-world clinical consultations from the perspective of both clinicians and patients. To scale AMIE across a multitude of disease conditions, specialties, and scenarios, they developed a novel self-play-based simulated diagnostic dialogue environment with automated feedback mechanisms to enrich and accelerate its learning process. The team also introduced an inference time chain-of-reasoning strategy to improve AMIE’s diagnostic accuracy and conversation quality. Finally, #AMIE was tested prospectively in real examples of multi-turn dialogue by simulating consultations with trained actors. This session was presented by Mike Schäkermann – Research Scientist, Google at #Healthcare #NLPSummit 2024 Watch an entire video here: https://lnkd.in/dRVgBRyq #HealthcareNLP #NLPLab #LargeLanguageModels #MedicalAIApplications, #AIinHealthcare #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp

It’s tomorrow! - ‘Fast, Cheap, Scalable: Open-Source Document Understanding with Spark NLP’ webinar on Wednesday, June 26, 2024, @ 2 pm ET by Danilo Burbano Acuña, our Software and Machine Learning Engineer. This talk introduces the latest capabilities of the open-source #SparkNLP library for running #LLM inference as an integral part of text or image processing pipelines. We’ll show code examples of how you can build common solutions easily and effectively, as well as speed & cost benchmarks – both versus commercial LLM #APIs and other open-source text processing solutions. This talk is intended for practicing data scientists and #AI engineers who are interested in production-grade solutions that are faster, cheaper, and more scalable that otherwise possible today, using only free & open-source tools. Register now: https://lnkd.in/dYmwurQf #GenerativeAI #HealthcareAI #MedicalLLMs #nlp #naturallanguageprocessing #DataScience #DataEngineering #DataAnalysis #DataInsights #TextProcessing #DeepLearning #DataScience

Moshe presented Intel Labs’ #fastRAG, a framework designed to facilitate the building of retrieval augmented generative pipelines. Its main goal is to make retrieval augmented generation as efficient as possible through the use of state-of-the-art and efficient retrieval and generative models. The framework includes a variety of sparse and dense retrieval models, as well as different extractive and generative information processing models. fastRAG aims to provide researchers and developers with a comprehensive tool-set for exploring and advancing the field of retrieval augmented generation. This session was presented by Moshe Wasserblat – NLP Research Manager at Intel at #Healthcare #NLPSummit 2024 Watch an entire video here: https://lnkd.in/dqd_ByRP #RAG #ResponsibleNLP #ResponsibleAI #HealthcareNLP #LargeLanguageModels #MedicalAIApplications, #AIinHealthcare #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp

By integrating powerful regular expression capabilities into a scalable NLP framework like #SparkNLP, the extraction of insights from text in #healthcare becomes more efficient and effective, even with large datasets. The #RegexMatcherInternal in Spark NLP provides a rule-based approach that enables users to define and apply custom #regexrules, empowering them to accurately extract specific patterns from text data. This solution is particularly beneficial in healthcare settings where precision and accuracy are crucial for data analysis, decision-making, and improving overall patient care outcomes, making it a versatile and invaluable tool for driving innovation and efficiency in the healthcare domain. Read more: https://hubs.li/Q02CWC590 #ai #generativeai #largelanguagemodels #ethicalai #modeltesting #modelevaluation #datascience

In the absence of a fully integrated electronic health record system, documents are an important source of health economic, and clinical information. For example, hospital discharge summaries contain useful health resource utilization information. Healthcare NLP tools are used to extract information from these unstructured documents, but reaching regulatory-grade accuracy often requires augmenting them with human-in-the-loop workflows. Spryfox and Care-Connect team proposes a framework for quality assurance for such systems, using clinician-developed logic to filter and rank entities to be manually reviewed – thereby reducing workload while maintaining a high level of safety. The framework has been implemented on top of John Snow Labs’ #Healthcare NLP & LLM models and applied in real-world clinical data abstraction projects for synthetic control and risk stratification. This session was presented by Christian Debes – Co-Founder, Head of Data Analytics & AI at SPRYFOX, and Fiona Kiernan – Chief Economist, Care Connect at #Healthcare #NLPSummit 2024 Watch an entire video here: https://lnkd.in/dmBrmjrh #ResponsibleNLP #ResponsibleAI #HealthcareNLP #NLPLab #LargeLanguageModels #MedicalAIApplications, #AIinHealthcare #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp

The 2024 #GenerativeAI in #Healthcare Survey was conducted online for a period of 33 days, spanning from February 12 to March 15, 2024. The survey includes responses from a total of 304 participants, among which 196 individuals are employed by organizations actively engaged in evaluating, utilizing, or deploying Generative AI (#GenAI) technologies. The respondents were recruited through various channels, including online advertising campaigns, social media platforms, the Gradient Flow Newsletter, and collaborations with industry partners. Learn more with The 2024 Generative AI in Healthcare Survey: https://hubs.li/Q02CWNYq0 #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp #naturallanguageprocessing #DataScience #DataEngineering #DataAnalysis #DataInsights #TextProcessing #DeepLearning #DataScience

#GenerativeAI is transforming the #healthcare industry by offering advanced no-code solutions for data management. #MedicalLargeLanguageModels are at the forefront of this revolution, providing capabilities such as summarization, question-answering, and text generation. These models enhance the ability to process and analyze vast amounts of healthcare data, leading to more informed decision-making and ultimately, improved patient care. By streamlining workflows, medical professionals can focus more on patient outcomes and less on the intricacies of data handling. Explore the possibilities now: https://hubs.li/Q02CWHXj0 #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp #naturallanguageprocessing #DataScience #DataEngineering #DataAnalysis #DataInsights #TextProcessing #DeepLearning #DataScience

This session introduces Coalition for Health AI (CHAI), how it works with the US government and across the healthcare community, what it has built that you can use today, and how you can get involved. Examples focus on #GenerativeAI applications in #healthcare – including the specific risks and best practices to pay attention to when building them, including John Snow Labs’ contributions in the areas of fairness, equity, and bias mitigation. This session was presented by Nicoleta Economou – Algorithm-Based CDS Oversight Director at Duke University School of Medicine and Mwisa Chisunka, our Head of Government Programs at #Healthcare #NLPSummit 2024 Watch an entire video here: https://lnkd.in/dh4nJsjm #ResponsibleNLP #ResponsibleAI #HealthcareNLP #NLPLab #LargeLanguageModels #MedicalAIApplications, #AIinHealthcare #LLMs #HealthcareLLMs #nocode #GenerativeAI #HealthcareAI #MedicalLLMs #nlp

Join the world’s largest Applied #NLP, #LLM, and #GenerativeAI community at the #NLPSummit! Three days of immersive content including over 50 technical sessions, with focus days on #opensource, #healthcare, and #applications. Attend live Q&A sessions with the speakers, connect with others through networking features, and access all content on-demand after the event. Register now: https://hubs.li/Q02CWBLR0 #ai #generativeai #largelanguagemodels #ethicalai #modeltesting #modelevaluation