<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Olesya Melnichenko | Harshita Sharma</title><link>https://www.drharshitasharma.com/authors/olesya-melnichenko/</link><atom:link href="https://www.drharshitasharma.com/authors/olesya-melnichenko/index.xml" rel="self" type="application/rss+xml"/><description>Olesya Melnichenko</description><generator>Source Themes Academic (https://sourcethemes.com/academic/)</generator><language>en-us</language><copyright>&amp;copy 2026 Dr. Harshita Sharma. All Rights Reserved.</copyright><lastBuildDate>Thu, 17 Sep 2026 00:00:00 +0000</lastBuildDate><image><url>img/map[gravatar:%!s(bool=false) shape:circle]</url><title>Olesya Melnichenko</title><link>https://www.drharshitasharma.com/authors/olesya-melnichenko/</link></image><item><title>Comprehensive Language-Image Pre-training for 3D Medical Image Understanding</title><link>https://www.drharshitasharma.com/publication/wald-comprehensive-2025/</link><pubDate>Thu, 17 Sep 2026 00:00:00 +0000</pubDate><guid>https://www.drharshitasharma.com/publication/wald-comprehensive-2025/</guid><description>&lt;h1 id="bibtex">BibTeX&lt;/h1>
&lt;pre>&lt;code>@inproceedings{wald2026comprehensive,
title={Comprehensive Language-Image Pre-training for 3D Medical Image Understanding},
author={Wald, Tassilo and Hamamci, Ibrahim Ethem and Gao, Yuan and Bond-Taylor, Sam and Sharma, Harshita and Ilse, Maximilian and Lo, Cynthia and Melnichenko, Olesya and Schwaighofer, Anton and Codella, Noel C. F. and Wetscherek, Maria Teodora and Maier-Hein, Klaus H. and Korfiatis, Panagiotis and Salvatelli, Valentina and Alvarez-Valle, Javier and P{\'e}rez-Garc{\'i}a, Fernando},
booktitle={Computer Vision -- ECCV 2026},
year={2026},
doi={10.1007/978-3-032-37624-4_24},
url={https://link.springer.com/chapter/10.1007/978-3-032-37624-4_24}
}
&lt;/code>&lt;/pre></description></item><item><title>Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting</title><link>https://www.drharshitasharma.com/publication/sharma-closing-2026/</link><pubDate>Fri, 21 Nov 2025 00:00:00 +0000</pubDate><guid>https://www.drharshitasharma.com/publication/sharma-closing-2026/</guid><description>&lt;h1 id="bibtex">BibTeX&lt;/h1>
&lt;pre>&lt;code class="language-bibtex">@article{sharma2025closing,
title={Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting},
author={Sharma, Harshita and Reynolds, Maxwell C. and Salvatelli, Valentina and Sykes, Anne-Marie G. and Horst, Kelly K. and Schwaighofer, Anton and Ilse, Maximilian and Melnichenko, Olesya and Bond-Taylor, Sam and P{\'e}rez-Garc{\'i}a, Fernando and Mugu, Vamshi K. and Chan, Alex and Colak, Ceylan and Swartz, Shelby A. and Nashawaty, Motassem B. and Gonzalez, Austin J. and Ouellette, Heather A. and Erdal, Selnur B. and Schueler, Beth A. and Wetscherek, Maria T. and Codella, Noel and Jain, Mohit and Bannur, Shruthi and Bouzid, Kenza and Castro, Daniel C. and Hyland, Stephanie and Korfiatis, Panos and Khandelwal, Ashish and Alvarez-Valle, Javier},
journal={arXiv preprint arXiv:2511.21735},
year={2025},
url={https://arxiv.org/abs/2511.21735}
}
&lt;/code>&lt;/pre></description></item><item><title>Data Scaling Laws for Radiology Foundation Models</title><link>https://www.drharshitasharma.com/publication/ilse-data-2025/</link><pubDate>Tue, 16 Sep 2025 00:00:00 +0000</pubDate><guid>https://www.drharshitasharma.com/publication/ilse-data-2025/</guid><description>&lt;h1 id="bibtex">BibTeX&lt;/h1>
&lt;pre>&lt;code>@article{ilse2025data,
title={Data Scaling Laws for Radiology Foundation Models},
author={Ilse, Maximilian and Sharma, Harshita and Schwaighofer, Anton and Bond-Taylor, Sam and P{\'e}rez-Garc{\'i}a, Fernando and Melnichenko, Olesya and Sykes, Anne-Marie G. and Horst, Kelly K. and Khandelwal, Ashish and Reynolds, Maxwell and Wetscherek, Maria T. and Codella, Noel C. F. and Alvarez-Valle, Javier and Panagiotis, Korfiatis and Salvatelli, Valentina},
journal={arXiv preprint arXiv:2509.12818},
year={2025},
doi={10.48550/arXiv.2509.12818},
url={https://arxiv.org/abs/2509.12818}
}
&lt;/code>&lt;/pre></description></item></channel></rss>