LLMs that are HIPAA Compliant!


Hello Reader,

Welcome to another edition of PYCAD newsletter where we cover interesting topics in Machine Learning and Computer Vision applied to Medical Imaging. The goal of this newsletter is to help you stay up-to-date and learn important concepts in this amazing field! I've got some cool insights for you below ↓

Now You Can Use Large Language Models that are HIPAA Compliant

People are finding ways to use large language models in all fields.

MedTech is no exception.

The amount of work required to skim through dozens of documents each day by clinicians is one area where LLMs can be of tremendous help.

I’ve had people from different medical backgounds explain to me some of their tedious administrative tasks and I am almost always sure that LLMs can help them one way or another.

However, many of them ask: but how can I use LLMs while being HIPAA compliant?

My answer is, use Fireworks AI.

Their platform is already HIPAA compliant.

This means that the LLM APIs you use on their platform are HIPAA compliant.

Here are some of the models that are already available on their platform:

  • Llama 3.3 70B Instruct.
  • Deepseek V3.
  • Stable Diffusion 3.5.
  • Whisper V3.

We've helped some of our clients build powerful applications in the medical field using such APIs. If your company is looking to build such a solution, feel free to respond to this email.

FDA Approvals driving AI Growth in Medical Imaging

The field of medical imaging continues to embrace artificial intelligence, with the number of FDA-approved AI tools skyrocketing to over 300 in recent years. From operational automations to cutting-edge diagnostic aids, these tools are transforming radiology and imaging workflows across the globe.

Why It Matters

AI adoption in medical imaging has surged, with over 50% of surveyed organizations actively using AI algorithms, up from just 17% in 2018. This rapid growth highlights AI’s potential to revolutionize diagnosis, enhance precision, and streamline clinical operations.

New Tools in Action

Innovations such as Aidoc’s CARE1 foundation model and Agfa’s integration of CARPL.ai into their imaging platform are leading the way. These advancements enable scalable AI adoption, allowing healthcare providers to harness AI’s power across various clinical domains.

With AI approvals accelerating and adoption growing, the future of medical imaging looks brighter than ever.

NVIDIA Partners with Mayo Clinic and Illumina to Advance AI in Healthcare

At JPM25, NVIDIA announced groundbreaking partnerships with Mayo Clinic, Illumina, and others to scale AI across healthcare. With Mayo Clinic, the focus is on accelerating pathology foundation models using NVIDIA’s DGX Blackwell AI systems and MONAI platform. Meanwhile, Illumina leverages NVIDIA’s tools for multiomics analysis, driving advancements in genomics and precision medicine.

These collaborations aim to revolutionize drug discovery, diagnostics, and biomedical research by unlocking new insights from complex datasets. With AI tools like BioNeMo and advanced foundation models, NVIDIA is setting a new standard for innovation in healthcare.


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We Can Help You with Your Next Medical Imaging Project

If your company or organization is looking to build a machine learning solution for a medical imaging problem, then feel free to reach out to us at:

contact@pycad.co

We can help you build a full ML solution from training to deployment with affordable rates!

You can check out some of the projects that we worked on here:

https://pycad.co/portfolio and some of our clients case studies here.


That's it for this week's edition, I hope you enjoyed it!

Machine Learning for Medical Imaging

👉 Learn how to build AI systems for medical imaging domain by leveraging tools and techniques that I share with you! | 💡 The newsletter is read by people from: Nvidia, Baker Hughes, Harvard, NYU, Columbia University, University of Toronto and more!

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