<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Digital Pathology Interview | Tissuepathology.com</title>
	<atom:link href="https://tissuepathology.com/category/digital-pathology-news/digital-pathology-interview/feed/" rel="self" type="application/rss+xml" />
	<link>https://tissuepathology.com</link>
	<description>Educational and informative</description>
	<lastBuildDate>Tue, 13 May 2025 13:01:35 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	

<image>
	<url>https://tissuepathology.com/wp-content/uploads/2017/07/cropped-Portrait_640x960px-32x32.png</url>
	<title>Digital Pathology Interview | Tissuepathology.com</title>
	<link>https://tissuepathology.com</link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>From the Proscia Blog: Q&#038;A: Engineering Excellence—How Concentriq LS Delivers a New Standard for Enterprise-Scale Performance</title>
		<link>https://tissuepathology.com/2025/05/13/from-the-proscia-blog-qa-engineering-excellence-how-concentriq-ls-delivers-a-new-standard-for-enterprise-scale-performance/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Tue, 13 May 2025 13:01:35 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Blogs]]></category>
		<category><![CDATA[Clinical Laboratories]]></category>
		<category><![CDATA[Clinical Pathology]]></category>
		<category><![CDATA[Data Management]]></category>
		<category><![CDATA[Digital Pathology Interview]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Laboratory Information Systems]]></category>
		<category><![CDATA[Laboratory Management & Operations]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Web/Tech]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[collaborative workflows]]></category>
		<category><![CDATA[complex annotations]]></category>
		<category><![CDATA[Concentriq LS]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[enterprise scalability]]></category>
		<category><![CDATA[high-resolution images]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[Proscia]]></category>
		<category><![CDATA[software engineering]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=23647</guid>

					<description><![CDATA[<p>As life sciences R&#38;D teams increasingly leverage digital pathology and AI to accelerate their precision medicine programs, Proscia’s Concentriq LS platform is handling unprecedented volumes of high-resolution images, complex annotations, and collaborative workflows. With the latest release, our engineering team has made significant strides in performance. I sat down with Taylor Tignino, Senior Software Engineer [&#8230;]</p>
The post <a href="https://tissuepathology.com/2025/05/13/from-the-proscia-blog-qa-engineering-excellence-how-concentriq-ls-delivers-a-new-standard-for-enterprise-scale-performance/">From the Proscia Blog: Q&A: Engineering Excellence—How Concentriq LS Delivers a New Standard for Enterprise-Scale Performance</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>Deep Bio and PathAI Collaborate to Drive AI-Powered Innovations in Digital Pathology</title>
		<link>https://tissuepathology.com/2024/11/22/deep-bio-and-pathai-collaborate-to-drive-ai-powered-innovations-in-digital-pathology/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Fri, 22 Nov 2024 12:08:09 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology Interview]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Health Technology Collaboration]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[International]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Press Release]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[Collaboration]]></category>
		<category><![CDATA[Deep Bio]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[PathAI]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[prostate cancer]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=23245</guid>

					<description><![CDATA[<p>Deep Bio: Integrating Deep Bio&#8217;s DeepDx Prostate Algorithm into PathAI&#8217;s AISight IMS Platform SEOUL, SOUTH KOREA, November 19, 2024 /EINPresswire.com/ &#8212; Deep Bio, a leader in artificial intelligence for digital pathology, announced a collaboration to integrate its prostate cancer analysis solution, DeepDx Prostate, with PathAI’s AISight®1 Image Management System (IMS). This collaboration combines Deep Bio’s clinically [&#8230;]</p>
The post <a href="https://tissuepathology.com/2024/11/22/deep-bio-and-pathai-collaborate-to-drive-ai-powered-innovations-in-digital-pathology/">Deep Bio and PathAI Collaborate to Drive AI-Powered Innovations in Digital Pathology</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>Aiosyn: Diana Rosentul explains the complexities of regulatory compliance for integrating AI-based solutions in the healthcare industry</title>
		<link>https://tissuepathology.com/2024/02/07/aiosyn-diana-rosentul-explains-the-complexities-of-regulatory-compliance-for-integrating-ai-based-solutions-in-the-healthcare-industry/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Wed, 07 Feb 2024 12:33:26 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Blogs]]></category>
		<category><![CDATA[Digital Pathology Interview]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[AI integration]]></category>
		<category><![CDATA[Aiosyn]]></category>
		<category><![CDATA[Diana Rosentul]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[Healthcare]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[regulations]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=22622</guid>

					<description><![CDATA[<p>From Aiosyn blog: Diana Rosentul, a Regulatory Affairs Specialist at Aiosyn, intricately manages the regulatory landscape associated with the integration of AI-based solutions within clinical and research institutions. Drawing upon her extensive background in Medical Sciences and the regulation of Medical Devices, Diana discusses challenges linked to staying up-to-date and shares her insights on handling [&#8230;]</p>
The post <a href="https://tissuepathology.com/2024/02/07/aiosyn-diana-rosentul-explains-the-complexities-of-regulatory-compliance-for-integrating-ai-based-solutions-in-the-healthcare-industry/">Aiosyn: Diana Rosentul explains the complexities of regulatory compliance for integrating AI-based solutions in the healthcare industry</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>Validation of PD-L1 AI model launches in six labs across the Netherlands</title>
		<link>https://tissuepathology.com/2021/03/22/validation-of-pd-l1-ai-model-launches-in-six-labs-across-the-netherlands/</link>
		
		<dc:creator><![CDATA[Dr. Keith J. Kaplan]]></dc:creator>
		<pubDate>Mon, 22 Mar 2021 13:05:41 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Business]]></category>
		<category><![CDATA[Case of the Month]]></category>
		<category><![CDATA[Clinical Laboratories]]></category>
		<category><![CDATA[Cloud Computing]]></category>
		<category><![CDATA[Data Management]]></category>
		<category><![CDATA[Device Manufacturers]]></category>
		<category><![CDATA[Digital Pathology Interview]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Informatics]]></category>
		<category><![CDATA[International]]></category>
		<category><![CDATA[Laboratory Informatics]]></category>
		<category><![CDATA[Marketing]]></category>
		<category><![CDATA[New Digital Imaging Technologies]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Vendor products]]></category>
		<category><![CDATA[aiforia AI]]></category>
		<category><![CDATA[Aiforia news]]></category>
		<category><![CDATA[aiforia software]]></category>
		<category><![CDATA[Featured]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=20012</guid>

					<description><![CDATA[<p>Labs in the Netherlands are joining together to launch an AI model validation study for PD-L1 scoring with a goal of multi-source domain adaptation. Introduction  Programmed death-ligand 1 (PDL1) is a protein that, when attached to T cells, prevent the immune system from killing cancer cells. Hence, PDL1 is used as a biomarker for tumor [&#8230;]</p>
The post <a href="https://tissuepathology.com/2021/03/22/validation-of-pd-l1-ai-model-launches-in-six-labs-across-the-netherlands/">Validation of PD-L1 AI model launches in six labs across the Netherlands</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
	</channel>
</rss>
