<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Healthcare AI on The Coders Blog</title><link>https://thecodersblog.com/tag/healthcare-ai/</link><description>Recent content in Healthcare AI on The Coders Blog</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 08 May 2026 08:31:10 +0000</lastBuildDate><atom:link href="https://thecodersblog.com/tag/healthcare-ai/index.xml" rel="self" type="application/rss+xml"/><item><title>MedQA: Fine-Tuning Clinical AI on AMD ROCm Without CUDA</title><link>https://thecodersblog.com/medqa-fine-tuning-clinical-ai-on-amd-rocm-2026/</link><pubDate>Fri, 08 May 2026 08:31:10 +0000</pubDate><guid>https://thecodersblog.com/medqa-fine-tuning-clinical-ai-on-amd-rocm-2026/</guid><description>&lt;p&gt;The healthcare industry stands on the precipice of an AI revolution, with Large Language Models (LLMs) poised to transform diagnostics, research, and patient care. However, the development and deployment of these sophisticated models have historically been tethered to proprietary hardware and software ecosystems, most notably NVIDIA&amp;rsquo;s CUDA. This dependency creates significant barriers to entry, limits innovation, and concentrates power within a single vendor. The advent of projects like MedQA, which demonstrates the successful fine-tuning of clinical AI models on AMD&amp;rsquo;s ROCm platform, signals a crucial shift towards democratizing advanced AI development. By eschewing CUDA and embracing an open ecosystem, MedQA isn&amp;rsquo;t just a technical achievement; it&amp;rsquo;s a statement of intent for a more accessible and competitive future in AI-driven healthcare.&lt;/p&gt;</description></item></channel></rss>