ODSC Denver Data Science

Pre-registration is REQUIRED.
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Topic: "Structuring Healthcare Data for usage with LLMs"

Getting your data RAG-ready for usage within LLM’s is no easy task. When your data consists of various patient chart document types (e.g. PDFs, HTML, PPT not to mention handwritten notes) you will have your work cut out for you. Join us in a workshop where we will structure healthcare patient data for usage with LLM’s. With the help of ‘unstuctured.io’ packages we will transform, clean, chunk, generate summaries and embeddings, then write our ‘structured’ healthcare data to a vector database (weaviate) where it can be used to interact with LLMs or Chatbots.

Training outline:

• Why is Structuring Healthcare Data so important when creating a Healthcare LLM?
• Discuss RAG Architecture for a future Healthcare LLM and/or Chatbot.
• What does Unstructured.io do?
• Why do we use a Vector Database?
• Steps to structuring our data for usage!
• Storing our structured data in Weaviate.
• Querying our newly structured healthcare data.

Speaker#1: Audrey Reznik Guidera, AI Platform Specialist Solution Architect | Red Hat
Audrey is an AI Platform Specialist Solution Architect working for Red Hat. She focuses on helping customers with managed services, AI/ML workloads and next-generation platforms. She holds a degree in Computer Information Systems and has been working in the IT Industry for over 20 years from full stack development to data science roles. Audrey is passionate about AI and in particular the current opportunities with AIML at the Edge and Open Source technologies.

Speaker#2: Bob Kozdemba, Principal Specialist Solution Architect | Red Hat
Bob is a career pre-sales engineer with hands-on experience using best of breed open source technologies to solve AI/ML workflow challenges including MLOps, RAG and generative AI.

ODSC Links:
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• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/

Pre-registration is REQUIRED.
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Topic: "Developing Equitable AI Diagnostics: A Technical Approach to Bias Mitigation"

In this talk, we will explore the critical need for fairness in AI-driven healthcare, with a focus on mitigating bias in machine learning models. As AI systems become more integrated into healthcare diagnostics, addressing the disparities in model performance across diverse ethnic groups is paramount. This session will present a technical deep dive into the challenges of bias in medical imaging datasets and the resulting impact on healthcare outcomes for underrepresented populations.

We will begin by defining the types of bias commonly found in machine learning models, with a case study in skin cancer detection. We will demonstrate how training on imbalanced datasets exacerbates disparities in diagnosing skin cancer across different racial groups. Attendees will gain insight into practical techniques for rectifying these biases, including data augmentation, fairness-aware algorithms, and advanced evaluation metrics designed to assess model equity.

In addition to discussing technical solutions, we will also address the limitations and ethical considerations surrounding bias mitigation in healthcare AI, highlighting the importance of interdisciplinary collaboration in creating equitable diagnostic tools. By the end of the session, participants will be equipped with the knowledge to implement fairness techniques in their own AI models, promoting better outcomes for all patient populations.

Speaker's bio: Laura Montoya, Founder and Managing Partner of Accel Impact Organizations

Laura is a tech leader focused on social impact and ethical AI. She founded Accel Impact Organizations, including Accel AI Institute and LXAI. With a background in biology, physics, and human development, Laura has worked at top tech companies like Intuit and has been a leader in tech diversity initiatives. She's a frequent speaker at industry conferences and has been featured in major publications.

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/