<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research and future on IMAGIX Healthtech | Technology that cares for caregivers</title><link>https://imagix.tech/en/categories/research-and-future/</link><description>Recent content in Research and future on IMAGIX Healthtech | Technology that cares for caregivers</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sat, 31 Oct 2026 10:00:00 -0300</lastBuildDate><atom:link href="https://imagix.tech/en/categories/research-and-future/index.xml" rel="self" type="application/rss+xml"/><item><title>What must a simulator prove before it is used to teach?</title><link>https://imagix.tech/en/articles/what-a-simulator-must-prove/</link><pubDate>Sat, 31 Oct 2026 10:00:00 -0300</pubDate><guid>https://imagix.tech/en/articles/what-a-simulator-must-prove/</guid><description>&lt;p&gt;A simulator can reproduce every button on the console, every screen and every sound of the equipment and still teach very little. Another, visually simple, can prepare someone better for the first time in front of a patient. The difference lies in how closely the decisions the student makes in the simulator match the ones they would make on the equipment.&lt;/p&gt;
&lt;p&gt;Before putting a simulator in a classroom, a teaching institution needs to know what it trains, how it measures what the student did and on what basis it claims that this result means anything.&lt;/p&gt;</description></item><item><title>AI in healthcare and the context where the model is used</title><link>https://imagix.tech/en/articles/why-context-matters-ai-healthcare/</link><pubDate>Fri, 12 Jun 2026 14:00:00 -0300</pubDate><guid>https://imagix.tech/en/articles/why-context-matters-ai-healthcare/</guid><description>&lt;p&gt;Artificial intelligence learns from examples: a model recognizes what was present in its training examples.&lt;/p&gt;
&lt;p&gt;In healthcare, differences in population, equipment, protocols, and access are part of the landscape. A solution developed far from this context may reach its limits when it enters daily practice.&lt;/p&gt;
&lt;h2 id="what-changes-between-where-the-model-learned-and-where-it-runs"&gt;What changes between where the model learned and where it runs&lt;/h2&gt;
&lt;p&gt;Adapting a system to Brazil involves knowing the equipment, the protocols, and the population of each service where it will run. In medical imaging, the difference between two services is recorded in the file itself.&lt;/p&gt;</description></item></channel></rss>