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<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>PolyU STAR</title><link>https://polyustar.github.io/</link><description>Recent content on PolyU STAR</description><generator>Hugo</generator><language>en-US</language><copyright>&copy; PolyU STAR, 2026</copyright><lastBuildDate>Tue, 25 Aug 2026 00:00:00 +0800</lastBuildDate><atom:link href="https://polyustar.github.io/index.xml" rel="self" type="application/rss+xml"/><item><title>Sheng NING</title><link>https://polyustar.github.io/member/sheng-ning/</link><pubDate>Tue, 25 Aug 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/sheng-ning/</guid><description/></item><item><title>Risk-Routed Implicit Boundary Refinement for Robust Ultrasound Image Segmentation</title><link>https://polyustar.github.io/publication/risk-routed-implicit-boundary-refinement-for-robust-ultrasound-image-segmentation/</link><pubDate>Thu, 23 Jul 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/risk-routed-implicit-boundary-refinement-for-robust-ultrasound-image-segmentation/</guid><description/></item><item><title>SonoX — Intelligent Ultrasound Image Analysis</title><link>https://polyustar.github.io/project/sonox/</link><pubDate>Mon, 22 Jun 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/project/sonox/</guid><description><h2 id="project-links">Project links</h2> <p><a href="https://polyustar.github.io/sonox/">Online App</a> <a href="https://github.com/PolyUSTAR/sonox">Frontend Mirror</a> <a href="https://github.com/jinggqu/SonoX">Source Code</a> <a href="https://doi.org/10.1109/tnnls.2026.3669814">Paper</a></p> <h2 id="overview">Overview</h2> <p>SonoX is an AI-empowered research platform for medical ultrasound image analysis. It provides browser-based workflows for lesion segmentation and classification, with support for lymph-node, breast, thyroid, and prostate ultrasound images.</p> <p>The application uses the Switch semi-supervised framework described in <em>Multiscale Switch for Semi-Supervised and Contrastive Learning in Medical Ultrasound Image Segmentation</em>.</p> <blockquote> <p>SonoX is a research demonstration and is not intended for clinical diagnosis.</p></description></item><item><title>Exercise Effect on Cerebral Artery Hemodynamic and Morphology in Stroke Patients: A Randomized Trial</title><link>https://polyustar.github.io/publication/exercise-effect-on-cerebral-artery-hemodynamic-and-morphology-in-stroke-patients/</link><pubDate>Wed, 20 May 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/exercise-effect-on-cerebral-artery-hemodynamic-and-morphology-in-stroke-patients/</guid><description/></item><item><title>Adapting vision-Language foundation model for next generation medical ultrasound image analysis</title><link>https://polyustar.github.io/publication/adapting-vision-language-foundation-model-for-next-generation-medical-ultrasound-image-analysis/</link><pubDate>Sat, 25 Apr 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/adapting-vision-language-foundation-model-for-next-generation-medical-ultrasound-image-analysis/</guid><description/></item><item><title>Multiscale Switch for Semi-Supervised and Contrastive Learning in Medical Ultrasound Image Segmentation</title><link>https://polyustar.github.io/publication/multiscale-switch-for-semi-supervised-and-contrastive-learning-in-medical-ultrasound-image-segmentation/</link><pubDate>Tue, 10 Mar 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/multiscale-switch-for-semi-supervised-and-contrastive-learning-in-medical-ultrasound-image-segmentation/</guid><description/></item><item><title>Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction</title><link>https://polyustar.github.io/publication/nanotherapies-for-atherosclerosis/</link><pubDate>Tue, 10 Mar 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/nanotherapies-for-atherosclerosis/</guid><description/></item><item><title>ChatGPT-5–Based large language model analysis versus an FDA-approved AI-CAD system for thyroid nodule ultrasound evaluation</title><link>https://polyustar.github.io/publication/chatgpt-5-based-large-language-model-analysis-versus-an-fda-approved-ai-cad-system/</link><pubDate>Sun, 01 Feb 2026 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/chatgpt-5-based-large-language-model-analysis-versus-an-fda-approved-ai-cad-system/</guid><description/></item><item><title>Intra- and Inter-Observer Reliability of ChatGPT-4o in Thyroid Nodule Ultrasound Feature Analysis Based on ACR TI-RADS: An Image-Based Study</title><link>https://polyustar.github.io/publication/intra--and-inter-observer-reliability-of-chatgpt-4o-in-thyroid-nodule-ultrasound-feature-analysis/</link><pubDate>Fri, 17 Oct 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/intra--and-inter-observer-reliability-of-chatgpt-4o-in-thyroid-nodule-ultrasound-feature-analysis/</guid><description/></item><item><title>Exploring the Potential of ChatGPT-4o in Thyroid Nodule Diagnosis Using Multi-Modality Ultrasound Imaging: Dual- vs. Triple-Modality Approaches</title><link>https://polyustar.github.io/publication/exploring-the-potential-of-chatgpt-4o-in-thyroid-nodule-diagnosis-using-multi-modality-ultrasound-imaging/</link><pubDate>Fri, 20 Jun 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/exploring-the-potential-of-chatgpt-4o-in-thyroid-nodule-diagnosis-using-multi-modality-ultrasound-imaging/</guid><description/></item><item><title>The Application of Deep Learning for Lymph Node Segmentation: A Systematic Review</title><link>https://polyustar.github.io/publication/the-application-of-deep-learning-for-lymph-node-segmentation/</link><pubDate>Mon, 02 Jun 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/the-application-of-deep-learning-for-lymph-node-segmentation/</guid><description/></item><item><title>Artificial intelligence performance in ultrasound-based lymph node diagnosis: a systematic review and meta-analysis</title><link>https://polyustar.github.io/publication/artificial-intelligence-performance-in-ultrasound-based-lymph-node-diagnosis-a-systematic-review-and-meta-analysis/</link><pubDate>Fri, 03 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/artificial-intelligence-performance-in-ultrasound-based-lymph-node-diagnosis-a-systematic-review-and-meta-analysis/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{han2025artificial, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Artificial intelligence performance in ultrasound-based lymph node diagnosis: a systematic review and meta-analysis}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Han, Xinyang and Qu, Jingguo and Chui, Man-Lik and Gunda, Simon Takadiyi and Chen, Ziman and Qin, Jing and King, Ann Dorothy and Chu, Winnie Chiu-Wing and Cai, Jing and Ying, Michael Tin-Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{BMC cancer}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{25}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{1}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{73}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2025}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Springer}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Jingguo QU</title><link>https://polyustar.github.io/member/jingguo-qu/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/jingguo-qu/</guid><description><p>Jingguo Qu received his B.Eng. degree from Eastern Liaoning University in 2018 and his M.Eng. degree from Southwest Petroleum University in 2023. He is currently pursuing a Ph.D. in the Department of Health Technology and Informatics at The Hong Kong Polytechnic University. His research interests include medical image processing, deep learning, and computer-aided diagnosis. He likes hiking and is a traveling enthusiast (Blog posts: <a href="https://jinggqu.github.io/posts/hiking-summary-2024/">2024</a>, <a href="https://jinggqu.github.io/posts/hiking-summary-2025">2025</a>), and he also is an amateur photographer (<a href="https://unsplash.com/@xvyn">Unsplash portfolio</a>).</p></description></item><item><title>Michael YING</title><link>https://polyustar.github.io/member/michael-ying/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/michael-ying/</guid><description><p>Prof. Michael YING was born in Hong Kong in 1971. He earned his Professional Diploma, MPhil, and PhD from the Hong Kong Polytechnic University in 1993, 1996, and 2002, respectively. After working as a diagnostic radiographer, he joined the university as an Assistant Professor in 1997, becoming a full Professor in 2020 and now serving as Associate Head of the Department of Health Technology and Informatics. He has authored over 160 journal papers, focusing on advanced ultrasound imaging and AI technologies. Prof. Ying is a Founding Fellow of the HKCRRT and was listed among the world&rsquo;s top 2% most-cited scientists in 2021, and received the gold medal in the 49th International Exhibition of Inventions of Geneva 2024.</p></description></item><item><title>Simon Takadiyi GUNDA</title><link>https://polyustar.github.io/member/simon-takadiyi-gunda/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/simon-takadiyi-gunda/</guid><description><p>Simon Takadiyi GUNDA received radiography and medical ultrasound degrees from the National University of Science and Technology in Zimbabwe in 2006, 2013, and 2021, followed by a Ph.D. from The Hong Kong Polytechnic University in 2025. He is a Registered Specialist Sonographer, Diagnostic Radiographer, and Medical Imaging Educator, with clinical radiography experience in Zimbabwe and Botswana and university teaching experience since 2014. He is currently a Postdoctoral Fellow at PolyU. His research focuses on innovative ultrasound methods for cerebrovascular assessment and stroke rehabilitation.</p></description></item><item><title>Tonghuan XIAO</title><link>https://polyustar.github.io/member/tonghuan-xiao/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/tonghuan-xiao/</guid><description/></item><item><title>Xinyang HAN</title><link>https://polyustar.github.io/member/xinyang-han/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/xinyang-han/</guid><description><p>Xinyang HAN received her B.Sc. degree in medical imaging technology from West China Medical School, Sichuan University, in 2021. She is currently pursuing a Ph.D. in medical science at The Hong Kong Polytechnic University. Her research interests include AI applications in medical imaging and ultrasound-based computer-aided diagnosis.</p></description></item><item><title>Yuqi YANG</title><link>https://polyustar.github.io/member/yuqi-yang/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/yuqi-yang/</guid><description/></item><item><title>Ziman CHEN</title><link>https://polyustar.github.io/member/ziman-chen/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/member/ziman-chen/</guid><description><p>Ziman CHEN is a Research Assistant Professor at The Hong Kong Polytechnic University. His research focuses on AI-enabled ultrasound diagnosis, including thyroid nodule classification, clinical decision support, and renal fibrosis assessment in chronic kidney disease. He develops and validates machine-learning approaches that combine clinical ultrasound expertise with medical AI to improve diagnostic accuracy and consistency.</p></description></item><item><title>Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease</title><link>https://polyustar.github.io/publication/interpretable-machine-learning-model-integrating-clinical-and-elastosonographic-features-to-detect-renal-fibrosis-in-asian-patients-with-chronic-kidney-disease/</link><pubDate>Thu, 26 Dec 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/interpretable-machine-learning-model-integrating-clinical-and-elastosonographic-features-to-detect-renal-fibrosis-in-asian-patients-with-chronic-kidney-disease/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024interpretable, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Wang, Yingli and Ying, Michael Tin Cheung and Su, Zhongzhen}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Journal of nephrology}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{37}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{4}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1027--1039}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Springer}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Ultrasonic renal length as an indicator of renal fibrosis severity in non-diabetic patients with chronic kidney disease</title><link>https://polyustar.github.io/publication/ultrasonic-renal-length-as-an-indicator-of-renal-fibrosis-severity-in-non-diabetic-patients-with-chronic-kidney-disease/</link><pubDate>Tue, 19 Nov 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/ultrasonic-renal-length-as-an-indicator-of-renal-fibrosis-severity-in-non-diabetic-patients-with-chronic-kidney-disease/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024ultrasonic, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Ultrasonic renal length as an indicator of renal fibrosis severity in non-diabetic patients with chronic kidney disease}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Jiang, Jun and Gunda, Simon Takadiyi and Han, Xinyang and Wu, Chaoqun and Ying, Michael Tin Cheung and Chen, Fei}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Clinical and Experimental Nephrology}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1--9}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Springer}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Assessing the feasibility of ChatGPT-4o and Claude 3-Opus in thyroid nodule classification based on ultrasound images</title><link>https://polyustar.github.io/publication/assessing-the-feasibility-of-chatgpt-4o-and-claude-3-opus-in-thyroid-nodule-classification-based-on-ultrasound-images/</link><pubDate>Fri, 11 Oct 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/assessing-the-feasibility-of-chatgpt-4o-and-claude-3-opus-in-thyroid-nodule-classification-based-on-ultrasound-images/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024assessing, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Assessing the feasibility of ChatGPT-4o and Claude 3-Opus in thyroid nodule classification based on ultrasound images}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Chambara, Nonhlanhla and Wu, Chaoqun and Lo, Xina and Liu, Shirley Yuk Wah and Gunda, Simon Takadiyi and Han, Xinyang and Qu, Jingguo and Chen, Fei and Ying, Michael Tin Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Endocrine}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1--9}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Springer}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography</title><link>https://polyustar.github.io/publication/improving-the-diagnostic-strategy-for-thyroid-nodules-a-combination-of-artificial-intelligence-based-computer-aided-diagnosis-system-and-shear-wave-elastography/</link><pubDate>Mon, 07 Oct 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/improving-the-diagnostic-strategy-for-thyroid-nodules-a-combination-of-artificial-intelligence-based-computer-aided-diagnosis-system-and-shear-wave-elastography/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024improving, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Improving the diagnostic strategy for thyroid nodules: a combination of artificial intelligence-based computer-aided diagnosis system and shear wave elastography}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Chambara, Nonhlanhla and Lo, Xina and Liu, Shirley Yuk Wah and Gunda, Simon Takadiyi and Han, Xinyang and Ying, Michael Tin Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Endocrine}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1--14}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Springer}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>The Diagnostic Accuracy of Transcranial Color-Coded Doppler Ultrasound Technique in Stratifying Intracranial Cerebral Artery Stenoses in Cerebrovascular Disease Patients: A Systematic Review and Meta-Analysis</title><link>https://polyustar.github.io/publication/the-diagnostic-accuracy-of-transcranial-color-coded-doppler-ultrasound-technique-in-stratifying-intracranial-cerebral-artery-stenoses-in-cerebrovascular-disease-patients-a-systematic-review-and-meta-analysis/</link><pubDate>Fri, 01 Mar 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/the-diagnostic-accuracy-of-transcranial-color-coded-doppler-ultrasound-technique-in-stratifying-intracranial-cerebral-artery-stenoses-in-cerebrovascular-disease-patients-a-systematic-review-and-meta-analysis/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{gunda2024diagnostic, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{The diagnostic accuracy of transcranial color-coded Doppler ultrasound technique in stratifying intracranial cerebral artery stenoses in cerebrovascular disease patients: a systematic review and meta-analysis}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Gunda, Simon Takadiyi and Yip, Jerica Hiu-Yui and Ng, Veronica Tsam-Kit and Chen, Ziman and Han, Xinyang and Chen, Xiangyan and Pang, Marco Yiu-Chung and Ying, Michael Tin-Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Journal of clinical medicine}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{13}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{5}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1507}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{MDPI}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>A Comparative Study of Transcranial Color-Coded Doppler (TCCD) and Transcranial Doppler (TCD) Ultrasonography Techniques in Assessing the Intracranial Cerebral Arteries Haemodynamics</title><link>https://polyustar.github.io/publication/a-comparative-study-of-transcranial-color-coded-doppler-tccd-and-transcranial-doppler-tcd-ultrasonography-techniques-in-assessing-the-intracranial-cerebral-arteries-haemodynamics/</link><pubDate>Sat, 10 Feb 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/a-comparative-study-of-transcranial-color-coded-doppler-tccd-and-transcranial-doppler-tcd-ultrasonography-techniques-in-assessing-the-intracranial-cerebral-arteries-haemodynamics/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{gunda2024comparative, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{A comparative study of transcranial color-coded Doppler (TCCD) and transcranial Doppler (TCD) ultrasonography techniques in assessing the intracranial cerebral arteries haemodynamics}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Gunda, Simon Takadiyi and Ng, Tsam Kit Veronica and Liu, Tsz-Ying and Chen, Ziman and Han, Xinyang and Chen, Xiangyan and Pang, Marco Yiu-Chung and Ying, Michael Tin-Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Diagnostics}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{14}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{4}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{387}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{MDPI}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Association of renal elasticity evaluated by real-time shear wave elastography with renal fibrosis in patients with chronic kidney disease</title><link>https://polyustar.github.io/publication/association-of-renal-elasticity-evaluated-by-real-time-shear-wave-elastography-with-renal-fibrosis-in-patients-with-chronic-kidney-disease/</link><pubDate>Sat, 10 Feb 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/association-of-renal-elasticity-evaluated-by-real-time-shear-wave-elastography-with-renal-fibrosis-in-patients-with-chronic-kidney-disease/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024association, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Association of renal elasticity evaluated by real-time shear wave elastography with renal fibrosis in patients with chronic kidney disease}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Wang, Yingli and Ying, Michael Tin Cheung and Su, Zhongzhen and Han, Xinyang and Gunda, Simon Takadiyi}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{British Journal of Radiology}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{97}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{1154}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{392--398}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">publisher</span>=<span style="color:#e6db74">{Oxford University Press}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Integrating shear wave elastography and estimated glomerular filtration rate to enhance diagnostic strategy for renal fibrosis assessment in chronic kidney disease</title><link>https://polyustar.github.io/publication/integrating-shear-wave-elastography-and-estimated-glomerular-filtration-rate-to-enhance-diagnostic-strategy-for-renal-fibrosis-assessment-in-chronic-kidney-disease/</link><pubDate>Tue, 02 Jan 2024 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/integrating-shear-wave-elastography-and-estimated-glomerular-filtration-rate-to-enhance-diagnostic-strategy-for-renal-fibrosis-assessment-in-chronic-kidney-disease/</guid><description><h2 id="citation">Citation</h2> <div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;-webkit-text-size-adjust:none;"><code class="language-bibtex" data-lang="bibtex"><span style="display:flex;"><span><span style="color:#a6e22e">@article</span>{chen2024integrating, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">title</span>=<span style="color:#e6db74">{Integrating shear wave elastography and estimated glomerular filtration rate to enhance diagnostic strategy for renal fibrosis assessment in chronic kidney disease}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">author</span>=<span style="color:#e6db74">{Chen, Ziman and Wang, Yingli and Gunda, Simon Takadiyi and Han, Xinyang and Su, Zhongzhen and Ying, Michael Tin Cheung}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">journal</span>=<span style="color:#e6db74">{Quantitative imaging in medicine and surgery}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">volume</span>=<span style="color:#e6db74">{14}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">number</span>=<span style="color:#e6db74">{2}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">pages</span>=<span style="color:#e6db74">{1766}</span>, </span></span><span style="display:flex;"><span> <span style="color:#a6e22e">year</span>=<span style="color:#e6db74">{2024}</span> </span></span><span style="display:flex;"><span>} </span></span></code></pre></div></description></item><item><title>Development and Deployment of a Novel Diagnostic Tool Based on Conventional Ultrasound for Fibrosis Assessment in Chronic Kidney Disease</title><link>https://polyustar.github.io/publication/development-and-deployment-of-a-novel-diagnostic-tool-based-on-conventional-ultrasound-for-fibrosis-assessment-in-chronic-kidney-disease/</link><pubDate>Sun, 26 Mar 2023 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/publication/development-and-deployment-of-a-novel-diagnostic-tool-based-on-conventional-ultrasound-for-fibrosis-assessment-in-chronic-kidney-disease/</guid><description/></item><item><title>Smart-CKD: a novel diagnostic platform for assessing moderate-to-severe renal fibrosis in chronic kidney disease</title><link>https://polyustar.github.io/project/ckd/</link><pubDate>Sun, 26 Mar 2023 00:00:00 +0800</pubDate><guid>https://polyustar.github.io/project/ckd/</guid><description><h2 id="githubpaperonline-app"><a href="https://github.com/PolyUSTAR/ckd">GitHub</a> <a href="https://www.academicradiology.org/article/S1076-6332(23)00091-0/fulltext">Paper</a> <a href="https://polyustar.github.io/ckd">Online APP</a></h2> <p><img src="https://github.com/PolyUSTAR/ckd/raw/main/resource/demo.png" alt="Smart-CKD"></p> <h2 id="abstract">Abstract</h2> <h3 id="rationale-and-objectives">Rationale and Objectives</h3> <p>Accurate identification of risk information about fibrosis severity is crucial for clinical decision-making and clinical management of patients with chronic kidney disease (CKD). This study aimed to develop an ultrasound (US)-derived computer-aided diagnosis tool for identifying CKD patients at high risk of developing moderate-severe renal fibrosis, in order to optimize treatment regimens and follow-up strategies.</p> <h3 id="materials-and-methods">Materials and Methods</h3> <p>A total of 162 CKD patients undergoing renal biopsies and US examinations were prospectively enrolled and randomly divided into training (n = 114) and validation (n = 48) cohorts. A multivariate logistic regression approach was employed to develop the diagnostic tool named S-CKD for differentiating moderate-severe renal fibrosis from mild one in the training cohort by integrating the significant variables, which were screened out from demographic characteristics and conventional US features via the least absolute shrinkage and selection operator regression algorithm. The S-CKD was then deployed as both an online web-based and an offline document-based, easy-to-use auxiliary device. In both the training and validation cohorts, the S-CKD&rsquo;s diagnostic performance was evaluated through discrimination and calibration. The clinical benefit of using S-CKD was revealed by decision curve analysis (DCA) and clinical impact curves.</p></description></item><item><title/><link>https://polyustar.github.io/about/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://polyustar.github.io/about/</guid><description><h1 id="sed-extemplo-conantur-et-cnosia-harundine-lyra">Sed extemplo conantur et Cnosia harundine lyra</h1> <h2 id="agros-metitur-venatibus-catenis-quippe-honorem-tuorum">Agros metitur venatibus catenis quippe honorem tuorum</h2> <p>Lorem markdownum finemque prunaque longe et sunt. Sed super aulaea in Paridis noctisque cubile? Iacit coetus, vastatoremque dedit; Vidi magna, recurvatis copia. Quod sit; per cingo tamen Hyperionis si vacat <strong>inclitus</strong> instabat curaque arma saxea, naturaeque pondere quaeque aer!</p> <ol> <li>Agros apertum aliis dominaeque rapidus</li> <li>Prima nulla est</li> <li>Hortatibus voto</li> </ol> <h2 id="anum-istis-praefertur-est">Anum istis praefertur est</h2> <p>Quaque coeptis lumina mea nuda dentes semine agitavit, caesique voluptas. Proque priori vultus est colle fuit manet manibusque Liber vulnus famulosque memorante dari. Aut quod ergo, oris simulasse. Ministros cogeret momordit aut tibi, posita non inhaesit sede vulnera sontes Phoebeos, faenilibus non rursus.</p></description></item><item><title/><link>https://polyustar.github.io/approach/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://polyustar.github.io/approach/</guid><description><h1 id="et-malis-vellet-tellus-deseruere-in-credant">Et malis vellet tellus deseruere in credant</h1> <h2 id="inde-sidera-moenia-lacertis-nomen-nostra-membra">Inde sidera moenia lacertis nomen nostra membra</h2> <p>Lorem markdownum miranti. Sonus faciunt omnibus frustra: illa possem ad regio Anubis tamen. Sustulerat debent fluviis herbis attollere rogus et formae nitentem avellere motis clipeus Achilles felix videam undas. <em>Posuit haec ipse</em> posse.</p> <p>Ore fame mons Olympi tantae <em>stringit</em> columbas proxima habebat, longius alta non. Haeserat gerunt detinuit genis est huc, dixit tam dumque nitidum.</p> <ol> <li>Cristata causam Triones moenia habentem subito utentem</li> <li>Astraea castris contentus nisi leve eum invia</li> <li>Inferiusque capta cognoscenda flaventi locuta notavi fallere</li> <li>Moriens scripsi ictus tuo cum</li> </ol> <p>Tarpeias insurgens summo sinistra vertice, in neve utroque exempla Cyparissus tanta tecti terras. Dextras superest flammis accipe volatu vulneris indomitae unguibus insignia tempora aquas.</p></description></item><item><title/><link>https://polyustar.github.io/mission/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://polyustar.github.io/mission/</guid><description><h1 id="auras-queritur-facientes-dixit-venti-sustinui">Auras queritur facientes dixit venti sustinui</h1> <h2 id="e-in-mora">E in mora</h2> <p>Lorem markdownum poenaque nuper destituit silendo quoniam, nec ait consorte membra, figuram hanc cum. Manifesta vitae facies exiguumque iunctam dictis. Vidit eadem, hanc cum descendit <strong>sinu</strong> misit quem fecit, positisque pastorve. Missus solos <em>potentia in</em> erant noctem est!</p> <pre><code>if (dvdProcessorVolume &lt; mpegProcess(slashdot, gigahertz)) { transferAnsiBotnet.and(logSoftware, hsfClipboardSubnet.queue_publishing( systemMemory, 5, yahoo)); } else { swappableIpv -= spoolingAdwareCrossplatform; extranetAppArchitecture(1, dtd_rpc_font(45, 67, development_sli)); } antivirus_ipv = touchscreenFiosGrep.portIcsDrive(zone_vista); bootExpression = 2 * sprite_dv + apache; if (cifsZone(status) &gt; wddm_cifs) { disk_access_www.halftone_plagiarism = 4; } else { domainFat(vectorCdnMalware, -2, hard.smartphone_e_wep(phreaking_memory, 5, kerningError)); address += troubleshooting; rdramRegistry(printerHoc); } </code></pre> <p>Ipsa namque impetus crinem nefandas, parant inmensum noviens specie vita. Ire locus quietis, amata occiderat Achaidas cervum quos pavit dissiluit an <a href="http://artenitido.org/non.html">loqui</a> consolantia fontes; <em>tenus quae</em>. Facit verumque per Pindusque paelice inmensi: vino exire, fuisse munera. Quam pars quod gravidi pennas: non illa et senex, et Iunone.</p></description></item><item><title/><link>https://polyustar.github.io/research/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://polyustar.github.io/research/</guid><description><h1 id="modo-est">Modo est</h1> <h2 id="non-sub-haedum-tenet">Non sub haedum tenet</h2> <p>Lorem markdownum esse diversa quoque vocavit, quam! Vires tibi axis dum spolium <em>vaticinor fulminis</em>, a dixere attrahit generisque tamen?</p> <ul> <li>Petit invergens iram praetendat iam</li> <li>Mecum res curva iunctura silvis hoc leonum</li> <li>Iacent gemitum quos</li> </ul> <h2 id="non-est-duram-mitis-sonat-proculcat-tumulos">Non est duram mitis sonat proculcat tumulos</h2> <p>Alce bimembres Dauni, cur ex voces referam adunco in sors. Manibusque poples prodidit lata tantum quem suos ratae Aeginae sederunt degenerat Bacchus descendere, patriisque ieiunia.</p></description></item><item><title/><link>https://polyustar.github.io/vacancy/vacancy1/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://polyustar.github.io/vacancy/vacancy1/</guid><description><p>You can write $\LaTeX$ and <em>Markdown</em> here.</p> <h1 id="minyae-adgnoscitque-fugiebat-parentis-ausum-superos-huius">Minyae adgnoscitque fugiebat parentis ausum superos huius</h1> <h2 id="ait-erili-meruisse-iactatis-omnibus-erat">Ait erili meruisse iactatis omnibus erat</h2> <p>Lorem markdownum natis, ipsi ipsi aut relictus saxo comitantibus aegro amori verba fugisse <strong>mira mortisque leones</strong>! Prior sui liquidissimus leve properandum totidem studio, refert <em>magno</em>, me quibus. Sternitur discordia summaque, si deus in undam et vulnere dirusque est felices pallam miserere curvamine comites. Tegumenque decipit suis, poscitur una dea sumus adnuerant, gerebat est edam plura. Armigerae Cyllenius freti vaga adeunda, rura undas, equarum ubi non laetoque pice.</p></description></item></channel></rss>