<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[PULMO AI]]></title><description><![CDATA[THORACIS]]></description><link>https://detectedu.wixsite.com/thoracis-ai/blog</link><generator>RSS for Node</generator><lastBuildDate>Wed, 03 Jun 2026 11:22:14 GMT</lastBuildDate><atom:link href="https://detectedu.wixsite.com/thoracis-ai/blog-feed.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Why Fusion Works: Cross-Modal Learning]]></title><description><![CDATA[Discover why combining microwave imaging and acoustic analysis achieves 99.3% accuracy—far beyond either modality alone—and what this means for clinical screening.]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/why-fusion-works-cross-modal-learning</link><guid isPermaLink="false">69d402ad11b9dfb4baa58a21</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 19:01:58 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/nsplsh_4e4b9051c2914e7f844300b1d93898dc~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item><item><title><![CDATA[XGBoost: The Magic Behind Our Fusion Model]]></title><description><![CDATA[Learn how XGBoost (eXtreme Gradient Boosting) combines microwave features and acoustic probabilities to achieve 99.3% accuracy in tumor detection.]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/xgboost-the-magic-behind-our-fusion-model</link><guid isPermaLink="false">69d40172838edf8f8dd3a290</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 18:58:20 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/nsplsh_5a69516b68493734313741~mv2_d_3456_2304_s_2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item><item><title><![CDATA[How YAMNet Works: From Sound Waves to 1024-D Embeddings]]></title><description><![CDATA[Explore how YAMNet converts lung sounds into 1024-dimensional embeddings, capturing wheezes, crackles, and breath patterns to classify respiratory diseases.]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/how-yamnet-works-from-sound-waves-to-1024-d-embeddings</link><guid isPermaLink="false">69d4004e072d140cb95c2d54</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 18:51:33 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/nsplsh_26b5b10dd2234198805c21b1f2f8615d~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item><item><title><![CDATA[Permittivity, Conductivity, and Loss Tangent: The Dielectric Trio]]></title><description><![CDATA[Discover the three key electromagnetic properties that distinguish tumors from healthy tissue—permittivity, conductivity, and loss tangent—and how PULMO-AI uses them for detection.]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/permittivity-conductivity-and-loss-tangent-the-dielectric-trio</link><guid isPermaLink="false">69d3ff4184368b484105f227</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 18:48:15 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/nsplsh_1f5d05c2fcf74a278528d1ac478292e2~mv2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item><item><title><![CDATA[Understanding IFFT: Revealing Hidden Tumor Reflections]]></title><description><![CDATA[Learn how the Inverse Fast Fourier Transform converts frequency-domain S21 data into time-domain reflections, helping PULMO-AI locate tumors by measuring signal delays.]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/understanding-ifft-revealing-hidden-tumor-reflections</link><guid isPermaLink="false">69d3fe33c53e2b8fe1249a74</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 18:43:40 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/nsplsh_334e717a724f4563584f51~mv2_d_6000_4000_s_4_2.jpg/v1/fit/w_1000,h_1000,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item><item><title><![CDATA[Maxwell's Equations: The Physics Behind Microwave Imaging]]></title><description><![CDATA[Learn the physics and functionality behind microwave imaging by mastering these essential equations]]></description><link>https://detectedu.wixsite.com/thoracis-ai/post/maxwell-s-equations-the-physics-behind-microwave-imaging</link><guid isPermaLink="false">69d3fbb0954483bc0388574f</guid><category><![CDATA[MWI]]></category><pubDate>Mon, 06 Apr 2026 18:38:22 GMT</pubDate><enclosure url="https://static.wixstatic.com/media/74165b_269d89527b624aee99bee4fad4dbf8d9~mv2.png/v1/fit/w_200,h_93,al_c,q_80/file.png" length="0" type="image/png"/><dc:creator>DetectED </dc:creator></item></channel></rss>