<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Benchmark on Rachid Youven Zeghlache</title><link>https://youvenz.github.io/tags/benchmark/</link><description>Recent content in Benchmark on Rachid Youven Zeghlache</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://youvenz.github.io/tags/benchmark/index.xml" rel="self" type="application/rss+xml"/><item><title>Benchmark &amp; Challenges</title><link>https://youvenz.github.io/research/benchmark-and-challenges/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://youvenz.github.io/research/benchmark-and-challenges/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;Progress in medical AI is only reproducible when the community shares standardised datasets, evaluation protocols, and leaderboards. I contribute to this infrastructure by co-organising international challenges and building open benchmarks that allow fair comparison of methods under identical conditions.&lt;/p&gt;
&lt;h2 id="mario-challenge--miccai-2024"&gt;MARIO Challenge — MICCAI 2024&lt;/h2&gt;
&lt;p&gt;The &lt;strong&gt;MARIO (Monitoring Age-Related Macular Degeneration Intelligence and Outcomes)&lt;/strong&gt; challenge was a satellite event at MICCAI 2024 in Marrakesh. It provided:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;A multi-modal longitudinal OCT dataset for AMD progression prediction&lt;/li&gt;
&lt;li&gt;Standardised train/validation/test splits with held-out labels for fair evaluation&lt;/li&gt;
&lt;li&gt;Two tracks: binary conversion prediction and interval-to-conversion regression&lt;/li&gt;
&lt;li&gt;Participation from international teams across 3 continents&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Results were presented at the MICCAI 2024 main conference. The challenge data and evaluation server remain publicly available for continued benchmarking.&lt;/p&gt;</description></item><item><title>MARIO AMD Progression Challenge</title><link>https://youvenz.github.io/projects/mario-challenge/</link><pubDate>Sun, 01 Sep 2024 00:00:00 +0000</pubDate><guid>https://youvenz.github.io/projects/mario-challenge/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;
&lt;p&gt;The &lt;strong&gt;MARIO AMD Progression Challenge&lt;/strong&gt; was held at MICCAI 2024 and focused on the automated assessment of &lt;strong&gt;Age-related Macular Degeneration (AMD)&lt;/strong&gt; progression using deep learning.&lt;/p&gt;
&lt;p&gt;We are pleased to announce the publication of our comprehensive analysis of the challenge results, and the corresponding dataset is now publicly available for the research community.&lt;/p&gt;
&lt;h2 id="research-focus"&gt;Research Focus&lt;/h2&gt;
&lt;p&gt;This challenge addressed two key clinical questions:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Progression prediction&lt;/strong&gt;: Will a patient&amp;rsquo;s AMD progress over the next 12 months?&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Visual acuity change&lt;/strong&gt;: Will the patient&amp;rsquo;s visual acuity improve, stabilise, or worsen?&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="dataset"&gt;Dataset&lt;/h2&gt;
&lt;p&gt;The MARIO dataset provides:&lt;/p&gt;</description></item></channel></rss>