PathAI

PathAI

Software Development

Boston, Massachusetts 58,855 followers

Improving patient outcomes with AI-powered pathology.

About us

PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning. We are a company of diverse employees with a wide range of backgrounds and experiences. Our world class team is passionate about solving challenging problems and making a huge impact. Our office is located in the heart of Fenway. PathAI was recently voted one of BBJ's Best Places to Work!

Website
http://www.pathai.com
Industry
Software Development
Company size
501-1,000 employees
Headquarters
Boston, Massachusetts
Type
Privately Held
Founded
2016
Specialties
artificial intelligence, pathology, digital pathology, oncology, immuno-oncology, auto immune disease, neurodegenerative disease, companion diagnostics, precision medicine, R&D, computational pathology, deep learning, software engineering, AI, Machine Learning, IBD, cancer research, oncology research, Drug Development, CRO , Clinical development, healthtech, and Artificial Intelligence

Locations

Employees at PathAI

Updates

  • View organization page for PathAI, graphic

    58,855 followers

    🌐 A team of #machinelearning engineers and scientists at PathAI have conducted a new interpretability analysis of PLUTO (PathoLogy Universal TransfOrmer), our novel #pathology-centric foundation model in a study titled “𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐛𝐢𝐨𝐥𝐨𝐠𝐢𝐜𝐚𝐥𝐥𝐲 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐟𝐞𝐚𝐭𝐮𝐫𝐞𝐬 𝐢𝐧 𝐚 𝐩𝐚𝐭𝐡𝐨𝐥𝐨𝐠𝐲 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥 𝐮𝐬𝐢𝐧𝐠 𝐬𝐩𝐚𝐫𝐬𝐞 𝐚𝐮𝐭𝐨𝐞𝐧𝐜𝐨𝐝𝐞𝐫𝐬” 📝 Read the preprint: https://lnkd.in/gjzMg2RM Our team used Sparse Autoencoders (SAEs) to analyze embeddings from PLUTO to uncover biologically interpretable features, such as plasma cell, lymphocyte counts, and other features. These representations evolved across the model’s layers, showcasing consistency across even non-biological factors, such as scanner type. Such biological representations were not found in generic vision models. This article highlights our ongoing work to utilize the latest #AI technology to advance medical imaging and fuel potential clinical applications. #MachineLearning #ArtificialIntelligence #DigitalPathology

    Learning biologically relevant features in a pathology foundation model using sparse autoencoders

    Learning biologically relevant features in a pathology foundation model using sparse autoencoders

    arxiv.org

  • View organization page for PathAI, graphic

    58,855 followers

    PathAI scientists and partners have recently published “𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐨𝐟 𝐚 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦 𝐢𝐧 𝐚 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐂𝐨𝐡𝐨𝐫𝐭 𝐟𝐨𝐫 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐨𝐟 𝐇𝐮𝐦𝐚𝐧 𝐄𝐩𝐢𝐝𝐞𝐫𝐦𝐚𝐥 𝐆𝐫𝐨𝐰𝐭𝐡 𝐅𝐚𝐜𝐭𝐨𝐫-2–𝐒𝐭𝐚𝐢𝐧𝐞𝐝 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐒𝐩𝐞𝐜𝐢𝐦𝐞𝐧𝐬 𝐢𝐧 𝐁𝐫𝐞𝐚𝐬𝐭 𝐂𝐚𝐧𝐜𝐞𝐫” in Archives of #Pathology and #LaboratoryMedicine. 📝 Read the publication: https://lnkd.in/gVQJBumU #BreastCancer biomarker assessment continues to be a critical component for #clinicaltrial enrollment and endpoint assessment as well as for optimal treatment determination in breast cancer patients. While manual scoring is currently the standard for predicting #HER2 #immunohistochemistry (IHC) status, there is an opportunity to improve inter-pathologist scoring variability and inconsistent #pathologylaboratory protocols (e.g., fixation, tissue processing, staining) that can affect HER2 staining and interpretation. In this paper, we detail the development of #AIPathology tools to aid in the quantification of HER2 expression, taking into account stain intensity and membrane completeness, tumor area and presence of artifacts. This #AI model can be used to identify and monitor trends over time both within and between laboratories and has the potential to improve assessments for HER2 scoring.

    Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2–Stained Clinical Specimens in Breast Cancer

    Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2–Stained Clinical Specimens in Breast Cancer

    meridian.allenpress.com

  • View organization page for PathAI, graphic

    58,855 followers

    🌐 We’re thrilled to present our latest AISight® #ImageManagementSystem platform update, designed to elevate your #pathology workflows and enhance your #digitalpathology viewing experience. Learn more about AISight®: https://lnkd.in/ef5NWxse Here are a few new features & highlights of the latest AISight® Platform Update: - 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐏𝐚𝐧𝐧𝐢𝐧𝐠 𝐌𝐨𝐝𝐞: New panning mode allows the slide to follow your mouse movements without holding down the mouse, reducing hand fatigue.  - 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐝 𝐂𝐚𝐬𝐞 𝐍𝐚𝐯𝐢𝐠𝐚𝐭𝐢𝐨𝐧: New button in the slide viewer and keyboard shortcut lets you move seamlessly to the next prioritized case–and in AISight® Live sessions, this feature will queue up the next case for review. - 𝐃𝐚𝐭𝐚 & 𝐈𝐧𝐭𝐞𝐫𝐨𝐩𝐞𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭𝐬: Specimen display at slide level, bulk ingest improvements, filter performance enhancements, 𝘢𝘯𝘥 𝘮𝘰𝘳𝘦. ✉️ Connect with us to demo AISight® today: digitaldx@pathai.com AISight® is for Research Use Only in the US; AISight® Dx is CE-IVD marked in the EEA, UK, and Switzerland. #AIPathology #AI #biotech #healthtech #histopathology

  • View organization page for PathAI, graphic

    58,855 followers

    Our latest #webinar "𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐏𝐚𝐭𝐡𝐨𝐥𝐨𝐠𝐲 𝐟𝐨𝐫 𝐌𝐀𝐒𝐇 & 𝐋𝐢𝐯𝐞𝐫 𝐃𝐢𝐬𝐞𝐚𝐬𝐞 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐚𝐧𝐝 𝐃𝐫𝐮𝐠 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭" is now available on demand! ⏯️ 💻 🔗 Watch the webinar: https://lnkd.in/eqxusN_j Discover the transformative role of #AIpathology tools in advancing drug development and providing unparalleled insights for MASH and liver disease. In this webinar, our experts explore how AI-driven tools can provide high-resolution characterization of the inflammatory microenvironment and fibrotic microarchitecture in liver #biopsies. 𝐖𝐇𝐀𝐓 𝐘𝐎𝐔 𝐖𝐈𝐋𝐋 𝐋𝐄𝐀𝐑𝐍  - Histological insights that can be uniquely captured by AI-powered #pathology - An inside look at building #AI tools specifically for liver disease research - Live demonstration of Liver Explore™  - #CaseStudies and guidance on leveraging AI-powered insights in MASH and liver disease - An overview of Liver Explore™’s versatility in MASH and non-MASH applications 𝘓𝘪𝘷𝘦𝘳 𝘌𝘹𝘱𝘭𝘰𝘳𝘦™ 𝘪𝘴 𝘧𝘰𝘳 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘜𝘴𝘦 𝘖𝘯𝘭𝘺. 𝘕𝘰𝘵 𝘧𝘰𝘳 𝘶𝘴𝘦 𝘪𝘯 𝘥𝘪𝘢𝘨𝘯𝘰𝘴𝘵𝘪𝘤 𝘱𝘳𝘰𝘤𝘦𝘥𝘶𝘳𝘦𝘴. 

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  • View organization page for PathAI, graphic

    58,855 followers

    Congratulations to our partners at Friends of Cancer Research and all of the authors on their recent findings presented at the San Antonio Breast Cancer Symposium #SABCS24. The Digital PATH project demonstrated how 10 AI-enabled #digitalpathology tools showed similar inter-AI agreement compared to inter-pathologist agreement in evaluating #HER2 status, a key marker for breast cancer treatment. By using a common set of digitized biopsy slides, this collaboration promotes consistency in HER2 testing, critical for guiding targeted antibody-drug conjugate (#ADC) therapies. These findings highlight the potential for #AIPathology and #PrecisionMedicine to pave the way for more precise and effective #BreastCancer treatments.

    View profile for Jeff Allen, graphic

    President & CEO, Friends of Cancer Research

    NEW RESULTS: New findings from our Digital PATH project showing the extent of agreement between 10 different AI-enabled digital pathology tools used to evaluate HER2 status were presented at the San Antonio Breast Cancer Symposium. HER2 is an important marker in breast cancer that can help determine the best course of treatment. Specialized targeted therapies called antibody drug conjugates (ADCs) can deliver potent anti-cancer medicines directly to targets, like HER2, on cancer cells. Advances in digital and computational pathology tools have enabled the identification of patients with low and ultralow HER2 expression that can benefit from these new targeted therapies - but optimal treatment requires accurate test results. Through the use of a common set of digitized biopsy slides, this unique collaboration compared the outputs from different tools. This provides a model to help ensure consistency in test results across different digital pathology tools and pave the way for the next generation of targeted ADC therapies. More about the Digital and Computational Pathology Tool Harmonization (Digital PATH) Project: https://lnkd.in/eAdT7d3m Many thanks to our collaborators in this innovative endeavor: Friends of Cancer Research, NCI Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), ZAS - Ziekenhuis aan de Stroom, Lunit Oncology, Panakeia, PathAI, University of North Carolina at Chapel Hill, Indica Labs, Caris Life Sciences, GSK, 4D Path, FDA, GA Green Consulting LLC, AstraZeneca, Bristol Myers Squibb, MOLECULAR CHARACTERIZATION LABORATORY at Frederick National Lab, KULIG CONSULTING LLC, BostonGene, Emory University, Amgen, Nucleai, Merck & Co., Inc. #AIOncology #SABCS24

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  • View organization page for PathAI, graphic

    58,855 followers

    We are live at the 11𝐭𝐡 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐏𝐚𝐭𝐡𝐨𝐥𝐨𝐠𝐲 & 𝐀𝐈 𝐂𝐨𝐧𝐠𝐫𝐞𝐬𝐬 in London.  Visit the PathAI team at Booth #9 to learn more about AISight® Image Management System, our central hub for case and image management equipped with best-in-class artificial intelligence tools to transform your histopathology lab operations. Meet with Max Zinner and Suzana Vega Harring MD MBA to discover how 𝐀𝐈𝐒𝐢𝐠𝐡𝐭 is revolutionizing pathology workflows to drive efficiency in the pathology lab.  Learn more about AISight®: https://lnkd.in/ef5NWxse #pathology #AI #AIpathology #biotech #histopathology #DigiPathLondon #AIhealthcare AISight® is for Research Use Only in the US; AISight® Dx is CE-IVD marked for primary diagnosis in the EEA, UK, and Switzerland.

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  • View organization page for PathAI, graphic

    58,855 followers

    Introducing the 𝐀𝐈𝐌-𝐈𝐇𝐂 𝐁𝐫𝐞𝐚𝐬𝐭 𝐏𝐚𝐧𝐞𝐥 𝐨𝐧 𝐀𝐈𝐒𝐈𝐠𝐡𝐭® 𝐈𝐦𝐚𝐠𝐞 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐒𝐲𝐬𝐭𝐞𝐦: Streamline breast cancer biomarker quantification on a single platform and implement this comprehensive AI-assisted panel to boost #pathology workflow efficiency. 🔗 Learn more: https://lnkd.in/eTAEE5xg This comprehensive panel supports pathologists by delivering accurate, consistent scoring of critical breast cancer biomarkers—HER2, ER, PR, and Ki-67—directly from routine #Immunohistochemistry (#IHC) images. The AIM-IHC Breast Panel also provides 𝐳𝐞𝐫𝐨-𝐜𝐥𝐢𝐜𝐤, 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 invasive cancer segmentation,  biomarker scoring, and provides associated overlays enabling faster, more precise insights, empowering pathologists to focus on critical decision-making. - 𝐅𝐮𝐥𝐥 𝐒𝐩𝐞𝐜𝐭𝐫𝐮𝐦 𝐁𝐢𝐨𝐦𝐚𝐫𝐤𝐞𝐫 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Consolidates analysis for key critical biomarkers HER2, ER, PR, and Ki-67 all in a single platform - 𝐅𝐚𝐬𝐭 & 𝐀𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐐𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Reliable, efficient analysis with zero-click, AI-powered invasive cancer detection, and biomarker quantification - no longer compromising accuracy for speed - 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞𝐝 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐈𝐌𝐒 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: AI-generated scoring of Breast Cancer IHC is fully integrated with the AISight® Image Management System reducing the time and effort required for manual assessments.  This release is part of PathAI’s ongoing mission to improve patient outcomes with AI-powered pathology. With the AIM-IHC Breast Panel and the expanding portfolio on the AISight® platform, we’re equipping pathologists with the tools needed to deliver precise, actionable insights. #AIPathology #AISight #Pathology #DigitalPathology #Diagnostics #DiagnosticResearch #IHC #Biotech #Biotechnology #AI #AIDigitalPathology 𝘈𝘐𝘔-𝘐𝘏𝘊 𝘉𝘳𝘦𝘢𝘴𝘵 𝘗𝘢𝘯𝘦𝘭, 𝘈𝘐𝘔-𝘏𝘌𝘙2, 𝘈𝘐𝘔-𝘌𝘙, 𝘈𝘐𝘔-𝘗𝘙, 𝘢𝘯𝘥 𝘈𝘐𝘔-𝘒𝘪-67 𝘢𝘳𝘦 𝘧𝘰𝘳 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘶𝘴𝘦 𝘰𝘯𝘭𝘺. 𝘕𝘰𝘵 𝘧𝘰𝘳 𝘶𝘴𝘦 𝘪𝘯 𝘥𝘪𝘢𝘨𝘯𝘰𝘴𝘵𝘪𝘤 𝘱𝘳𝘰𝘤𝘦𝘥𝘶𝘳𝘦𝘴. 𝘈𝘐𝘚𝘪𝘨𝘩𝘵 𝘪𝘴 𝘧𝘰𝘳 𝘙𝘦𝘴𝘦𝘢r𝘩 𝘜𝘴𝘦 𝘖𝘯𝘭𝘺 𝘪𝘯 𝘵𝘩𝘦 𝘜𝘚; 𝘈𝘐𝘚𝘪𝘨𝘩𝘵 𝘋𝘹 𝘪𝘴 𝘊𝘌-𝘐𝘝𝘋 𝘮𝘢𝘳𝘬𝘦𝘥 𝘪𝘯 𝘌𝘶𝘳𝘰𝘱𝘦, 𝘜𝘒 𝘢𝘯𝘥 𝘚𝘸𝘪𝘵𝘻𝘦𝘳𝘭𝘢𝘯𝘥.

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    We’re excited to launch the 𝐀𝐈𝐌-𝐈𝐇𝐂 𝐁𝐫𝐞𝐚𝐬𝐭 𝐏𝐚𝐧𝐞𝐥, 𝐛𝐫𝐢𝐧𝐠𝐢𝐧𝐠 𝐇𝐄𝐑2, 𝐄𝐑, 𝐏𝐑, 𝐚𝐧𝐝 𝐊𝐢-67 𝐛𝐢𝐨𝐦𝐚𝐫𝐤𝐞𝐫 𝐬𝐜𝐨𝐫𝐢𝐧𝐠 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫 𝐢𝐧𝐭𝐨 𝐨𝐧𝐞 𝐬𝐭𝐫𝐞𝐚𝐦𝐥𝐢𝐧𝐞𝐝 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦. Designed to enhance precision and efficiency, this AI-powered panel integrates seamlessly into our AISight® Image Management System (IMS). 🔗 Read the #PressRelease: https://lnkd.in/exChZJSX 𝐀𝐈𝐌-𝐈𝐇𝐂 𝐁𝐫𝐞𝐚𝐬𝐭 𝐏𝐚𝐧𝐞𝐥 𝐢𝐬 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐨 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐤𝐞𝐲 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐢𝐧 𝐛𝐫𝐞𝐚𝐬𝐭 𝐜𝐚𝐧𝐜𝐞𝐫 𝐛𝐢𝐨𝐦𝐚𝐫𝐤𝐞𝐫 𝐪𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧. This comprehensive panel provides pathologists with accurate, consistent scoring, enhancing precision and streamlining workflow efficiency. Adding to the existing AIM-HER2 Breast solution,  this consolidation of critical #breastcancer biomarkers into a single, pathologist-centric image management platform directly addresses the increasing demands of scoring breast cancer, providing standardized, reliable tools to support pathologists in the quantification of #HER2, ER, PR and Ki-67. “𝘛𝘩𝘦 𝘈𝘐𝘔-𝘐𝘏𝘊 𝘉𝘳𝘦𝘢𝘴𝘵 𝘗𝘢𝘯𝘦𝘭 𝘪𝘴 𝘵𝘩𝘦 𝘭𝘢𝘵𝘦𝘴𝘵 𝘴𝘵𝘦𝘱 𝘪𝘯 𝘰𝘶𝘳 𝘮𝘪𝘴𝘴𝘪𝘰𝘯 𝘵𝘰 𝘦𝘯𝘩𝘢𝘯𝘤𝘦 𝘈𝘐-𝘱𝘰𝘸𝘦𝘳𝘦𝘥 𝘴𝘤𝘰𝘳𝘪𝘯𝘨 𝘧𝘰𝘳 𝘬𝘦𝘺 𝘣𝘳𝘦𝘢𝘴𝘵 𝘤𝘢𝘯𝘤𝘦𝘳 𝘣𝘪𝘰𝘮𝘢𝘳𝘬𝘦𝘳𝘴. 𝘉𝘺 𝘴𝘵𝘳𝘦𝘢𝘮𝘭𝘪𝘯𝘪𝘯𝘨 𝘵𝘩𝘦 𝘲𝘶𝘢𝘯𝘵𝘪𝘧𝘪𝘤𝘢𝘵𝘪𝘰𝘯 𝘱𝘳𝘰𝘤𝘦𝘴𝘴, 𝘵𝘩𝘦 𝘱𝘢𝘯𝘦𝘭 𝘦𝘯𝘢𝘣𝘭𝘦𝘴 𝘱𝘢𝘵𝘩𝘰𝘭𝘰𝘨𝘪𝘴𝘵𝘴 𝘵𝘰 𝘮𝘢𝘬𝘦 𝘧𝘢𝘴𝘵𝘦𝘳, 𝘮𝘰𝘳𝘦 𝘱𝘳𝘦𝘤𝘪𝘴𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴.” said Andrew Beck, CEO of PathAI. This release highlights PathAI’s commitment to improving pathology workflow efficiency, speed, and accuracy. As the AISight® Image Management System continues to expand with new solutions, #pathologists gain access to a comprehensive suite of tools that streamline the assessment process, accelerating decision-making and reducing time spent on manual tasks. Contact us to learn more about the AIM-IHC Breast Panel: digitaldx@pathai.com #AIPathology #AISight #Pathology #DigitalPathology #Diagnostics #DiagnosticResearch #IHC #Biotech #Biotechnology #AI #AIDigitalPathology #IMS 𝘈𝘐𝘔-𝘐𝘏𝘊 𝘉𝘳𝘦𝘢𝘴𝘵 𝘗𝘢𝘯𝘦𝘭, 𝘈𝘐𝘔-𝘏𝘌𝘙2, 𝘈𝘐𝘔-𝘌𝘙, 𝘈𝘐𝘔-𝘗𝘙, 𝘢𝘯𝘥 𝘈𝘐𝘔-𝘒𝘪-67 𝘢𝘳𝘦 𝘧𝘰𝘳 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘶𝘴𝘦 𝘰𝘯𝘭𝘺. 𝘕𝘰𝘵 𝘧𝘰𝘳 𝘶𝘴𝘦 𝘪𝘯 𝘥𝘪𝘢𝘨𝘯𝘰𝘴𝘵𝘪𝘤 𝘱𝘳𝘰𝘤𝘦𝘥𝘶𝘳𝘦𝘴. 𝘈𝘐𝘚𝘪𝘨𝘩𝘵 𝘪𝘴 𝘧𝘰𝘳 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘜𝘴𝘦 𝘖𝘯𝘭𝘺 𝘪𝘯 𝘵𝘩𝘦 𝘜𝘚; 𝘈𝘐𝘚𝘪𝘨𝘩𝘵 𝘋𝘹 𝘪𝘴 𝘊𝘌-𝘐𝘝𝘋 𝘮𝘢𝘳𝘬𝘦𝘥 𝘪𝘯 𝘌𝘶𝘳𝘰𝘱𝘦, 𝘜𝘒 𝘢𝘯𝘥 𝘚𝘸𝘪𝘵𝘻𝘦𝘳𝘭𝘢𝘯𝘥.

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    We’re heading to the 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐏𝐚𝐭𝐡𝐨𝐥𝐨𝐠𝐲 𝐚𝐧𝐝 𝐀𝐈 𝐂𝐨𝐧𝐠𝐫𝐞𝐬𝐬 in London, December 11-12th!  #DigiPathLondon Visit us at 𝐁𝐨𝐨𝐭𝐡 #9 to see how 𝐀𝐈𝐒𝐢𝐠𝐡𝐭®, our image management system with a growing menu of AI products, is optimizing 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 and 𝐞𝐧𝐡𝐚𝐧𝐜𝐢𝐧𝐠 𝐜𝐨𝐥𝐥𝐚𝐛𝐨𝐫𝐚𝐭𝐢𝐨𝐧 in some of the 𝐰𝐨𝐫𝐥𝐝’𝐬 𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐩𝐚𝐭𝐡𝐨𝐥𝐨𝐠𝐲 𝐥𝐚𝐛𝐬.  🗓️ 𝐖𝐡𝐞𝐧: December 11-12th 📍 𝐖𝐡𝐞𝐫𝐞: Hilton London Metropole 🌐 𝐕𝐢𝐞𝐰 𝐭𝐡𝐞 𝐩𝐫𝐨𝐠𝐫𝐚𝐦:  https://lnkd.in/gPsfc3FS #digitalpathology #aipathology #aiheathcare #anatomicpathology 𝘈𝘐𝘚𝘪𝘨𝘩𝘵® 𝘪𝘴 𝘧𝘰𝘳 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘜𝘴𝘦 𝘖𝘯𝘭𝘺 𝘪𝘯 𝘵𝘩𝘦 𝘜𝘚; 𝘈𝘐𝘚𝘪𝘨𝘩𝘵 𝘋𝘹 𝘪𝘴 𝘊𝘌-𝘐𝘝𝘋 𝘪𝘯 𝘌𝘶𝘳𝘰𝘱𝘦 𝘢𝘯𝘥 𝘜𝘒𝘊𝘈 𝘪𝘯 𝘜𝘒

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    📝 PathAI scientists have recently published an article in 𝐍𝐚𝐭𝐮𝐫𝐞'𝐬 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐟𝐢𝐜 𝐑𝐞𝐩𝐨𝐫𝐭𝐬 titled "𝑨 𝒇𝒆𝒂𝒔𝒊𝒃𝒊𝒍𝒊𝒕𝒚 𝒔𝒕𝒖𝒅𝒚 𝒖𝒔𝒊𝒏𝒈 𝒒𝒖𝒂𝒏𝒕𝒊𝒕𝒂𝒕𝒊𝒗𝒆 𝒂𝒏𝒅 𝒊𝒏𝒕𝒆𝒓𝒑𝒓𝒆𝒕𝒂𝒃𝒍𝒆 𝒉𝒊𝒔𝒕𝒐𝒍𝒐𝒈𝒊𝒄𝒂𝒍 𝒂𝒏𝒂𝒍𝒚𝒔𝒆𝒔 𝒐𝒇 𝒄𝒆𝒍𝒊𝒂𝒄 𝒅𝒊𝒔𝒆𝒂𝒔𝒆 𝒇𝒐𝒓 𝒂𝒖𝒕𝒐𝒎𝒂𝒕𝒆𝒅 𝒄𝒆𝒍𝒍 𝒕𝒚𝒑𝒆 𝒂𝒏𝒅 𝒕𝒊𝒔𝒔𝒖𝒆 𝒂𝒓𝒆𝒂 𝒄𝒍𝒂𝒔𝒔𝒊𝒇𝒊𝒄𝒂𝒕𝒊𝒐𝒏" which details the development of #AIPathology tools to empower histological assessments of #CeliacDisease. The diagnosis of #celiacdisease relies heavily on #histological assessment, our team developed a fully automated, explainable #AI model that quantitatively characterizes celiac histology directly from H&E-stained biopsy slides. In this paper, we detail the development of #AIPathology tools for characterizing celiac disease and how our model can identify cells, tissue types, and artifacts while distinguishing key features such as intraepithelial lymphocytes and surrogates of villous atrophy, and crypt hyperplasia. These quantitative features show strong correlations with modified Marsh (Marsh–Oberhuber) scores, and have the potential to enable more consistent and precise assessments. This innovative approach holds promise for improving diagnostics, monitoring treatment responses, and supporting clinical trials. 🔗 Read more about how this breakthrough advances histological precision in celiac disease: https://lnkd.in/gY7V4Ua7 #AIinPathology #Pathology #PrecisionMedicine #IBD 

    A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification - Scientific Reports

    A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification - Scientific Reports

    nature.com

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