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		<title>Tempus Study Published in Nature Medicine Demonstrates Best-in-Class Performance of PRISM2 Across Diagnostic and Prognostic Applications</title>
		<link>https://tissuepathology.com/2026/08/27/tempus-study-published-in-nature-medicine-demonstrates-best-in-class-performance-of-prism2-across-diagnostic-and-prognostic-applications/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Thu, 27 Aug 2026 13:04:38 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Press Release]]></category>
		<category><![CDATA[Publications]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[Diagnostics Prognostics]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Nature Medicine]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[Publication]]></category>
		<category><![CDATA[Tempus AI]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24640</guid>

					<description><![CDATA[<p>Tempus’ multimodal foundation model offers diagnostic-grade precision for cancer detection and unlocks broader applications predicting biomarker status and patient prognosis CHICAGO, August 4, 2026 — Tempus AI, Inc. (NASDAQ: TEM), a technology company leading the adoption of AI to advance precision medicine and patient care, today announced study results demonstrating that PRISM2, a multimodal slide-level pathology [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/08/27/tempus-study-published-in-nature-medicine-demonstrates-best-in-class-performance-of-prism2-across-diagnostic-and-prognostic-applications/">Tempus Study Published in Nature Medicine Demonstrates Best-in-Class Performance of PRISM2 Across Diagnostic and Prognostic Applications</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>Optiscan Imaging Advances Head and Neck Cancer Study Ahead of Schedule</title>
		<link>https://tissuepathology.com/2026/07/21/optiscan-imaging-advances-head-and-neck-cancer-study-ahead-of-schedule/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Tue, 21 Jul 2026 11:30:50 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[International]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[head cancer]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[live imaging]]></category>
		<category><![CDATA[neck cancer]]></category>
		<category><![CDATA[Optiscan]]></category>
		<category><![CDATA[Pathology]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24564</guid>

					<description><![CDATA[<p>Optiscan Imaging pushes Stage 2 of head and neck cancer live-imaging study ahead of schedule, accelerating clinical validation and potential FDA submissions. Optiscan Imaging (ASX: OIL) has begun Stage 2 of its first-in-human head and neck cancer imaging study at St John of God Murdoch Hospital in Perth ahead of schedule. The hospital’s Human Research Ethics [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/07/21/optiscan-imaging-advances-head-and-neck-cancer-study-ahead-of-schedule/">Optiscan Imaging Advances Head and Neck Cancer Study Ahead of Schedule</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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		<title>Mayo Clinic study shows AI can help clinicians identify brain tumor risks</title>
		<link>https://tissuepathology.com/2026/06/25/mayo-clinic-study-shows-ai-can-help-clinicians-identify-brain-tumor-risks/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Thu, 25 Jun 2026 12:54:00 +0000</pubDate>
				<category><![CDATA[Anatomic Pathology]]></category>
		<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Press Release]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[brain tumor]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Mayo Clinic]]></category>
		<category><![CDATA[meningioma]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[study]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24513</guid>

					<description><![CDATA[<p>ROCHESTER, Minn. — Mayo Clinic researchers and collaborators have shown that an artificial intelligence (AI) tool can analyze routine pathology slides to help clinicians classify meningiomas, the most common primary brain tumor in adults, and better understand a patient’s risk of tumor recurrence. The study, published in The Lancet Digital Health, demonstrates that deep learning models can support the extraction of [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/06/25/mayo-clinic-study-shows-ai-can-help-clinicians-identify-brain-tumor-risks/">Mayo Clinic study shows AI can help clinicians identify brain tumor risks</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>ASCO: Now and Then</title>
		<link>https://tissuepathology.com/2026/06/11/asco-now-and-then/</link>
		
		<dc:creator><![CDATA[Dr. Keith J. Kaplan]]></dc:creator>
		<pubDate>Thu, 11 Jun 2026 18:00:28 +0000</pubDate>
				<category><![CDATA[Advocacy]]></category>
		<category><![CDATA[Anatomic Pathology]]></category>
		<category><![CDATA[Business]]></category>
		<category><![CDATA[Clinical Laboratories]]></category>
		<category><![CDATA[Clinical Pathology]]></category>
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		<category><![CDATA[Health Technology Collaboration]]></category>
		<category><![CDATA[Histology]]></category>
		<category><![CDATA[Humor]]></category>
		<category><![CDATA[Informatics]]></category>
		<category><![CDATA[Laboratory Informatics]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Microscopy]]></category>
		<category><![CDATA[Molecular Pathology]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Personal]]></category>
		<category><![CDATA[Reports]]></category>
		<category><![CDATA[Science]]></category>
		<category><![CDATA[Whole slide]]></category>
		<category><![CDATA[ASCO]]></category>
		<category><![CDATA[conferences]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24484</guid>

					<description><![CDATA[<p>In medical school I drove a cab at night to make ends meet. I rented the medallion from a guy for $50 and kept the difference I made. The Army paid me $692 a month stipend on the Health Professions Scholarship and the studio apartment in downtown Chicago was $1000/month. I wasshort over $300 a [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/06/11/asco-now-and-then/">ASCO: Now and Then</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>Call for papers: Breast cancer biomarkers in diagnostic and translational pathology – Breast Cancer: Targets and Therapy</title>
		<link>https://tissuepathology.com/2026/05/20/call-for-papers-breast-cancer-biomarkers-in-diagnostic-and-translational-pathology-breast-cancer-targets-and-therapy/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Wed, 20 May 2026 11:28:40 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Image Analysis]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[breast cancer]]></category>
		<category><![CDATA[Breast Cancer: Targets and Therapy]]></category>
		<category><![CDATA[call for papers]]></category>
		<category><![CDATA[diagnostic pathology]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[Pathology]]></category>
		<category><![CDATA[taylor & francis]]></category>
		<category><![CDATA[translational pathology]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24430</guid>

					<description><![CDATA[<p>Taylor &#38; Francis is pleased to invite you to submit your work to an upcoming Article Collection on “Breast cancer biomarkers in diagnostic and translational pathology” in the journal Breast Cancer: Targets and Therapy. This Article Collection will focus on investigating immunohistochemical and molecular biomarker testing in breast cancer, with particular emphasis on optimizing reproducibility and [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/05/20/call-for-papers-breast-cancer-biomarkers-in-diagnostic-and-translational-pathology-breast-cancer-targets-and-therapy/">Call for papers: Breast cancer biomarkers in diagnostic and translational pathology – Breast Cancer: Targets and Therapy</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
			</item>
		<item>
		<title>American Center for Cancer Research: DNA methylation &#8220;fingerprints&#8221; identify primary sites in metastatic cancers</title>
		<link>https://tissuepathology.com/2026/04/21/american-center-for-cancer-research-dna-methylation-fingerprints-identify-primary-sites-in-metastatic-cancers/</link>
		
		<dc:creator><![CDATA[Erica Goodpaster]]></dc:creator>
		<pubDate>Tue, 21 Apr 2026 13:47:18 +0000</pubDate>
				<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[Digital Pathology News]]></category>
		<category><![CDATA[Medical Research]]></category>
		<category><![CDATA[Pathology News]]></category>
		<category><![CDATA[Reports]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[American Center for Cancer Research]]></category>
		<category><![CDATA[cancer]]></category>
		<category><![CDATA[digital pathology]]></category>
		<category><![CDATA[DNA]]></category>
		<category><![CDATA[image analysis]]></category>
		<category><![CDATA[metastatic cancers]]></category>
		<category><![CDATA[methylation]]></category>
		<category><![CDATA[Pathology]]></category>
		<guid isPermaLink="false">https://tissuepathology.com/?p=24363</guid>

					<description><![CDATA[<p>A machine learning model analyzing CpG-based DNA methylation accurately predicted the origin of many different cancer types in patients with cancers of unknown primary (CUP), according to research presented at the American Association for Cancer Research (AACR) Annual Meeting 2026, held April 17-22. CUP are metastatic malignancies in which the primary cancer site could not [&#8230;]</p>
The post <a href="https://tissuepathology.com/2026/04/21/american-center-for-cancer-research-dna-methylation-fingerprints-identify-primary-sites-in-metastatic-cancers/">American Center for Cancer Research: DNA methylation “fingerprints” identify primary sites in metastatic cancers</a> first appeared on <a href="https://tissuepathology.com">Tissuepathology.com</a>.]]></description>
		
		
		
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