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DTSTART;TZID=Europe/London:20260601T140000
DTEND;TZID=Europe/London:20260601T150000
DTSTAMP:20260826T183559
CREATED:20260519T104944Z
LAST-MODIFIED:20260519T104944Z
UID:100121394-1780322400-1780326000@www.pathologynews.com
SUMMARY:TIA Centre Seminar Series – Co-evolving Computational Pathology: From Interactive Foundation Models (VISTA-PATH) to Agentic Medical Image Analysis (TissueLab)
DESCRIPTION:0000Days00Hrs00Min00SecThe Tissue Image Analytics (TIA) Centre hosts a seminar series for those interested in computational pathology. The series invites researchers and leaders in computational pathology and related fields to present their work and foster thought-provoking discussions. \nThis seminar features Dr Peixian Liang and Songhao Li from the University of Pennsylvania\, USA. \nAbstract\nComputational pathology is rapidly moving beyond static\, single-task predictors toward interactive systems that can segment\, reason\, and quantify tissue morphology under expert supervision. In this talk\, we present two complementary pillars of this transition from our group. First\, we introduce VISTA-PATH\, an interactive foundation model for histopathology image segmentation designed to resolve heterogeneous tissue structures\, incorporate expert feedback\, and generate pixel-level segmentations that are directly meaningful for clinical interpretation. Trained on over 1.6 million image–mask–text triplets spanning 9 organs and 93 tissue classes\, VISTA-PATH outperforms existing segmentation foundation models and enables clinically relevant biomarkers\, such as the Tumor Interaction Score (TIS)\, which shows a strong association with patient survival. Second\, we present TissueLab\, an open\, co-evolving agentic system (tissuelab.org) for end-to-end medical image analysis. TissueLab unifies foundation models and analytical tools within a modular tool graph\, including VISTA-PATH for interactive segmentation\, and translates LLM-generated plans into executable operations. Through tool-level\, strategy-level\, and workflow-level co-evolution\, it achieves over 90% accuracy in cancer cell quantification within 10-30 minutes of expert feedback\, improves lymph-node metastasis correlation from 0.827 to 0.933\, and reaches a macro-AUC of 0.838 on tubule formation scoring\, outperforming human-orchestrated workflows and state-of-the-art VLMs. \nRegister NowBio\nPeixian Liang is a Postdoctoral Researcher at the University of Pennsylvania\, working with Prof. Zhi Huang. She received her Ph.D. degree in Computer Science from the University of Notre Dame\, Notre Dame\, IN\, USA\, in 2023. Her research focuses on developing innovative AI/ML methods to advance medicine. She is particularly interested in building foundation models and computational frameworks to assist pathologists\, reduce variability in diagnosis\, and identify clinically relevant morphologic biomarkers. Her work aims to advance AI-driven approaches for more precise diagnosis\, prognosis\, and clinical and biological discovery. Songhao Li is a first-year Ph.D. student in Electrical and Systems Engineering at the University of Pennsylvania\, advised by Prof. Zhi Huang. He received his M.S. in Computer Science from New York University in 2025 and brings a strong full-stack and system-engineering background from prior roles in industry. His research focuses on agentic AI\, human–AI collaboration\, and ML/DL for medicine\, aiming to bridge AI research and clinical practice through transparent\, interactive\, and continuously learning systems. 
URL:https://www.pathologynews.com/event/tia-centre-seminar-series-co-evolving-computational-pathology-from-interactive-foundation-models-vista-path-to-agentic-medical-image-analysis-tissuelab/
LOCATION:Online
CATEGORIES:Live Online Webinar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260611T140000
DTEND;TZID=Europe/London:20260611T150000
DTSTAMP:20260826T183559
CREATED:20260507T085125Z
LAST-MODIFIED:20260514T082706Z
UID:100121023-1781186400-1781190000@www.pathologynews.com
SUMMARY:Two-part Webinar Series: Human Brilliance\, Augmented: Mastering Medical Information Overload with RAG and Second Brains. - Part 2
DESCRIPTION:0000Days00Hrs00Min00SecThis webinar will start at 2pm BST\, 9am EST \nIn this two-part webinar series\, Dr Soufiane Azdad and Dr Matthew Cecchini explore how AI is not here to replace the pathologist\, but to act as a powerful tool that augments human brilliance. \nEpisode 2 – The Augmented Lab: From Education to the Grossing Room\nPart 4 – Transforming Medical Education \nGenerating educational outputs directly from the second brain — interactive study aids\, flashcards\, quizzes\, and visual concept maps for medical students and residents. Journal club automation: scanning\, triaging\, and summarizing new literature from targeted journals. \nPart 5 – The Augmented Pathology Workflow \nHow AI-powered knowledge systems pair with physical workflow innovations (e.g.\, computer vision in automated pre-analytical steps) to create the pathology lab of the future. Emphasis on privacy-first\, on-premises architecture. \n*All sessions will be presented in English. \nRegister NowSpeakers\nDr Soufiane Akdad & Dr Matthew Cecchini
URL:https://www.pathologynews.com/event/two-part-webinar-series-human-brilliance-augmented-mastering-medical-information-overload-with-rag-and-second-brains-part-2/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/05/Two-part-Webinar-Series-Human-Brilliance-Augmented-Mastering-Medical-Information-Overload-with-RAG-and-Second-Brains.-–-Part-1.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260611T150000
DTEND;TZID=Europe/London:20260611T160000
DTSTAMP:20260826T183559
CREATED:20260521T140652Z
LAST-MODIFIED:20260521T140652Z
UID:100121460-1781190000-1781193600@www.pathologynews.com
SUMMARY:Aligning Display Expectations in Digital Pathology: Research Insights\, Tips and Tricks
DESCRIPTION:0000Days00Hrs00Min00SecThis webinar will start at  10AM EDT\, 7AM PDT\, 8AM MDT\, 4PM CET\, 3PM BST \nDigital pathology workflows – whether diagnostic or for research purposes – depend on what you can see\, how consistently you can see it\, and how confidently you can act on it. In this webinar\, Amanda Hemmerich (IQVIA Laboratories) and Tom Kimpe (Barco) discuss display-related considerations for digital pathology and reflect on findings from a recent peer-reviewed article they published together with ADC Therapeutics. \nWhat we’ll cover in this webinar\n\nKey display considerations in digital pathology\nHow study insights can inform expectations and decision-making\nPractical questions to ask yourself when evaluating displays for your lab environment\n\nThe webinar is ideal for… \nPathologists\, lab managers\, researchers and anyone involved in managing whole slide imaging workflows \nRegister NowPresenters\nAmanda Hemmerich\nGlobal Director of Digital Pathology Innovation\nIQVIA Laboratories \nBoard certified in anatomic and clinical pathology and cytopathology\, Dr Amanda Hemmerich leads the global digital pathology strategy\, including implementation of end-to-end workflows that meet regulatory standards and partnerships with image analysis vendors. She also assists with testing at the Genomics Center of Excellence and the Anatomic Pathology Translational Science and Innovation Laboratory in the Raleigh-Durham area of North  Carolina. Dr Hemmerich has expertise in developing digital pathology techniques\, managing large-scale pathology services\, test validation and operationalisation. \nTom Kimpe\nVP Technology & Innovation\nBarco \nTom Kimpe holds a Master of Science degree in computer science engineering\, a Ph.D. in electrical engineering/medical imaging from Ghent University\, and an MBA from the Vlerick Management School in Belgium. He is inventor of several patents\, and (co-)author of tens of scientific publications in the domain of medical imaging & displays\, visualization\, human vision perception\, quality assurance and calibration\, optics\, image processing and artificial intelligence. Dr. Kimpe leads Barco’s healthcare innovation activities\, collaborating with universities\, research institutes\, hospitals\, and medical device companies.
URL:https://www.pathologynews.com/event/aligning-display-expectations-in-digital-pathology-research-insights-tips-and-tricks/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/05/Aligning-Display-Expectations-in-Digital-Pathology-Research-Insights-Tips-and-Tricks.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260611T160000
DTEND;TZID=Europe/London:20260611T170000
DTSTAMP:20260826T183559
CREATED:20260518T091149Z
LAST-MODIFIED:20260518T091149Z
UID:100121338-1781193600-1781197200@www.pathologynews.com
SUMMARY:What is New in HALO®\, HALO AI\, and HALO Link 4.3?
DESCRIPTION:This webinar will start at 8:00 PDT\, 11:00 EDT\, 16:00 BST \nLearn about the exciting new features in the 4.3 versions of HALO\, HALO AI\, and HALO Link!\nSummary\nJoin Indica Labs for an exciting webinar highlighting the latest innovations in HALO\, HALO AI\, and HALO Link 4.3. In this new version\, users can create clean independent slide copies\, enabling blinded workflows without duplicating the image on the storage drive. Users will also experience smoother viewing of svs images with the support of native cloud storage for this image type. \nIn HALO 4.3\, object data generated in different analysis modules can be customized to display and save only what the user needs. Quality of life improvements include enhancements in real-time display of annotation dimensions\, improved notifications\, and display of additional metadata for ome.tiff images. Additionally\, the HALO High Dimensional Analysis module has been updated to include interactive links between feature heatmaps and images\, assisting cluster identification via easier selection and display of the cells in each cluster. \nHALO AI 4.3 offers per-class reporting of phenotypes from a masking/phenotyper pipeline eliminating the need for modules to generate this type of result. In addition\, users can batch launch training sessions and view cross entropy values across sessions\, capabilities that can streamline and inform classifier training. \nIn version 4.3\, HALO Link supports large studies containing tens of thousands of images with performant slide navigation and image viewing. The new capability to add slides to studies directly from search accelerates study creation in version 4.3. For admins\, configurable system-level task management—with visual workflow tracking—and bulk user actions simplify user management and save time\, especially when managing larger teams. \n\n\nLearning Objectives\n\n\n\n\n\nLearn about the new slide copy workflow with independent slide copies    \nLearn about the per–class reporting of phenotyper results in HALO AI masking/phenotyper pipelines \nLearn about improved performance with large studies in HALO Link \nLearn about system–managed customizable tasks  \n\n\n\nRegister Now\nPresenter\n\nDr. Noemi Kedei\nDirector of Product\, Life Sciences \nIndica Labs  \nNoemi Kedei earned an MD degree from University Medical School of Debrecen\, Hungary. She did her postdoctoral training and worked later as a staff scientist in the Laboratory of Cancer Biology and Genetics\, NCI. Her research focused on identifying mechanisms involved in the differential effects of natural compounds and their engineered derivatives acting on protein kinase Cs (PKCs)\, validated targets for anti-cancer treatment. In 2018 she joined the Collaborative Protein Technology Resources (OSTR\, CCR\, NCI) core facility to implement a variety of spatial protein and transcriptomics technologies\, and lead related operations as services to NCI investigators. Noemi provided expertise for development of project based customized antibody protein panels for detection of 40-60 protein targets at single cell level in tissue sections using the CODEX/Phenocycler fusion technology\, and ensured optimal and efficient instrument use. In addition\, she advised and supported users on tools for quantitative image analysis combining different AI-enabled HALO modules and NCI developed pipelines for downstream analysis. Noemi joined Indica Labs as Director of Product – Life Sciences in May\, 2025. 
URL:https://www.pathologynews.com/event/what-is-new-in-halo-halo-ai-and-halo-link-4-3/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/05/What-is-New-in-HALO®-HALO-AI-and-HALO-Link-4.3.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260616T160000
DTEND;TZID=Europe/London:20260616T170000
DTSTAMP:20260826T183559
CREATED:20260528T094030Z
LAST-MODIFIED:20260528T094725Z
UID:100121789-1781625600-1781629200@www.pathologynews.com
SUMMARY:Powering ADC Development with the New HALO® ADC Target Scoring Module
DESCRIPTION:0000Days00Hrs00Min00SecThis webinar will start at 8:00 PDT\, 11:00 EDT\, 16:00 BST \nLearn about the new HALO module designed to streamline analysis for ADC-focused assays\n\n\n\n\nSummary\n\n\n\n\nIn this webinar\, Indica Labs will discuss advancements in antibody-drug conjugates (ADC) therapies and the growing need for reproducible methods to quantify expression and spatial context. This presentation introduces the ADC Target Scoring analysis module in HALO®\, designed to streamline analysis for ADC-focused assays. \nBy integrating AI membrane and nuclear segmentation with built-in spatial analysis\, the ADC Target Scoring workflow enables Quantitative Continuous Scoring (QCS) strategies. Expanded membrane compartment detection and additional optical density metrics provide data for bioinformatic pipelines\, supporting analysis of varied membrane and cytoplasmic staining patterns relevant to ADC biology. \nAttendees will gain insight into how simplified inputs and AI detection reduce manual tuning. A live demonstration will guide participants through the full workflow\, including cell segmentation\, Threshold Assist\, customization of object-level outputs\, and visualization of quantitative and spatial results. \n\n\n\n\n\n\n\n\nLearning Objectives\n\n\n\n\n\nExplore how antibody-drug conjugate (ADC) assays are reshaping targeted therapies\, and how quantitative image analysis can inform development and response prediction \nSee how Indica Labs’ new ADC Target Scoring module bridges image analysis and downstream data interpretation\nUnderstand how AI segmentation and integrated spatial analysis enables QCS approaches  \nWalk through a complete workflow in HALO\, from cell segmentation and Threshold Assist to customizable outputs and result visualization\n\n\n\n\n\nRegister Now\nPresenter\n\nEmily Gamble\nHALO Analysis Product Manager\nIndica Labs  \nEmily Gamble has a background in education and neuroscience. She received her M.S. in Neuroscience from Tulane University in New Orleans\, LA. Emily joined the Product Management team at Indica Labs as the HALO Product Specialist in 2020 and was promoted to her current role as HALO Analysis Product Manager in 2025. Emily works closely with customers and software engineers at all stages of product development to enhance the image analysis experience across the range of HALO modules.
URL:https://www.pathologynews.com/event/powering-adc-development-with-the-new-halo-adc-target-scoring-module/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/05/Powering-ADC-Development-with-the-New-HALO®-ADC-Target-Scoring-Module.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260622T140000
DTEND;TZID=Europe/London:20260622T150000
DTSTAMP:20260826T183559
CREATED:20260610T111947Z
LAST-MODIFIED:20260610T111947Z
UID:100122062-1782136800-1782140400@www.pathologynews.com
SUMMARY:How Close Are We to Personalized Treatment Decisions with Causal Machine Learning?
DESCRIPTION:0000Days00Hrs00Min00SecThe Tissue Image Analytics (TIA) Centre hosts a seminar series for those interested in computational pathology. The series invites researchers and leaders in computational pathology and related fields to present their work and foster thought-provoking discussions. \nThis seminar features Octavia Ciora and Maresa Schröder from LMU Munich\, Munich\, Germany. \nAbstract\nUnderstanding the efficacy and safety of treatments is crucial for optimizing patient outcomes. However\, patients respond differently to the same treatment due to biological\, clinical\, or contextual factors\, which highlights the need for personalized clinical evidence to guide treatment decisions. Causal machine learning offers a promising way to do so by combining causal inference principles with flexible ML models to estimate personalized treatment effects. In this talk\, we present findings from a scoping review of 70 clinical studies applying causal machine learning in personalized medicine. We assessed 41 key methodological choices\, including clinical context\, model\, validation\, heterogeneity analysis\, and clinical translation. We show how these causal ML is currently used\, how their results are validated\, and where important gaps remain. Finally\, we propose a validation framework with methodological recommendations to promote reliable clinical evidence generation. \nRegister NowBio\nOctavia Ciora is a second-year PhD student in computer science at LMU Munich\, supervised by Prof. Stefan Feuerriegel. She holds bachelor’s and master’s degrees in bioinformatics from the Technical University of Munich and LMU Munich. Her research lies at the intersection of causal machine learning and healthcare. Her work focuses on developing machine learning-based frameworks for clinical decision-support\, treatment effect estimation from electronic health records\, and personalized treatment recommendations for oncology. Maresa Schröder is a final-year PhD student in computer science at LMU Munich\, supervised by Prof. Stefan Feuerriegel. She holds a mathematics master’s degree from the Technical University of Munich and bachelor’s degree in economics and mathematics from the University of Mannheim. Her research interest lies in causal machine learning with a special focus on reliable treatment effect estimation\, such as the development of uncertainty quantification and robust estimation methods while ensuring ethical constraints. Furthermore\, she is interested in developing advanced causal methods for medical applications and strategic decision-making.
URL:https://www.pathologynews.com/event/how-close-are-we-to-personalized-treatment-decisions-with-causal-machine-learning/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/png:https://www.pathologynews.com/wp-content/uploads/2026/06/TIA-Centre-Seminar-Series-How-Close-Are-We-to-Personalized-Treatment-Decisions-with-Causal-Machine-Learning.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260625T160000
DTEND;TZID=UTC:20260625T170000
DTSTAMP:20260826T183559
CREATED:20260506T083327Z
LAST-MODIFIED:20260506T083327Z
UID:100120968-1782403200-1782406800@www.pathologynews.com
SUMMARY:From Images to Insights: Getting Started with RNAscope™ Image Analysis in HALO®
DESCRIPTION:0000Days00Hrs00Min00SecThis webinar will start at 8:00\, PDT\, 11:00 EDT\, 16:00 BST \nDiscover commonly used tools to get started today with RNAscope™ image analysis in HALO®\n\n\n\n\nSummary\n\n\n\n\nJoin us for this 1-hour webinar to learn about the latest RNAscope™ assays from Bio-Techne Spatial and to see a live demonstration of RNAscope™ image analysis using the HALO® platform from Indica Labs. This webinar will demonstrate how to effectively leverage HALO’s ISH and FISH modules for RNAscope analysis\, as well as how to leverage neural networks in HALO AI to improve cell segmentation and classify tissue regions. In addition\, select HALO modules and workflows that are commonly used with RNAscope™ image analysis will be demonstrated. Attendees will leave with practical guidance and best practices for building scalable\, reproducible RNAscope analysis workflows in HALO\, making this session ideal for researchers and core facilities working with both brightfield and fluorescence assays.  \n\n\n\n\n\n\n\n\nLearning Objectives\n\n\n\n\n\nOverview of the RNAscope technology\, key assays and applications  \nLearn about HALO modules for brightfield and fluorescent RNAscope™ image analysis \nDiscover how HALO AI advances RNAscope™ image analysis with superior nuclear segmentation and custom tissue classification  \nLearn about HALO tools commonly used in RNAscope™ analysis such as the TMA (Tissue Microarray) Module and the Spatial Analysis module \n\n\n\n\n\nRegister Now\nPresenters\n\nSpencer Revill\, MSc\nField Applications Scientist\nIndica Labs  \nSpencer Revill is a Field Application Scientist at Indica Labs supporting digital pathology and image analysis with a background in biotechnology and medical sciences. Prior to joining Indica\, he managed a translational research core facility and conducted graduate research in lung pathology using digital image analysis. Spencer now works closely with customers to support evaluations\, proof‑of‑concept studies\, and adoption of HALO\, HALO AI\, and HALO Link across a wide range of research applications. His work focuses on helping researchers translate complex image data into reliable\, reproducible insights using digital pathology.  \nAnushka Dikshit\, PhD\nSenior Manager\, Spatial Biology Applications\nBio-Techne \nAnushka is a Senior Manager and group leader for the Applications Marketing Management team at Bio-Techne Spatial with background in cancer research and immuno-oncology. Anushka and her team are focused on expanding the applications of the RNAscope technology across different research areas through internal and external collaborations. Prior to working for Bio-Techne\, she was involved in identifying novel therapeutic targets for melanoma as a postdoctoral fellow at Duke University. She obtained her doctoral degree from Southern Illinois University\, School of Medicine in Molecular Physiology. 
URL:https://www.pathologynews.com/event/from-images-to-insights-getting-started-with-rnascope-image-analysis-in-halo/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/05/From-Images-to-Insights-Getting-Started-with-RNAscope™-Image-Analysis-in-HALO®.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260629T140000
DTEND;TZID=Europe/London:20260629T150000
DTSTAMP:20260826T183559
CREATED:20260619T105137Z
LAST-MODIFIED:20260619T105137Z
UID:100122240-1782741600-1782745200@www.pathologynews.com
SUMMARY:TIA Centre Seminar Series – Pathology Foundation Models for Text-prompted Segmentation and Precision Oncology
DESCRIPTION:0000Days00Hrs00Min00SecThe Tissue Image Analytics (TIA) Centre hosts a seminar series for those interested in computational pathology. The series invites researchers and leaders in computational pathology and related fields to present their work and foster thought-provoking discussions. \nThis seminar features Dr Junlin Hou from The Hong Kong University of Science and Technology\, Hong Kong. \nAbstract\nComputational pathology is rapidly moving from task-specific image analysis toward foundation models that enable scalable\, generalizable disease diagnosis and clinical decision support. In this talk\, I will first present our recent work\, PathSegmentor\, a foundation model that enables flexible\, text-prompted segmentation across diverse pathological entities. Beyond segmentation\, I will also provide an overview of our broader efforts in pathology foundation models\, including image enhancement\, whole-slide representation learning\, benchmarking\, and agentic AI systems. These works aim to advance computational pathology toward more precise\, interpretable\, and clinically useful AI for precision oncology. \nRegister NowBio\nDr. Junlin Hou is a Post-doctoral Fellow in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology (HKUST). She obtained her Ph.D. from the School of Computer Science at Fudan University in 2023. She has published 30+ papers in top-tiered journals and conferences\, including Nature Computational Science\, Nature Biomedical Engineering\, IEEE TMI\, MICCAI\, CVPR\, etc. She has served as a guest editor for CMIG and J. Imaging\, and as a reviewer for 15+ journals and conferences. She also led the team winning 10+ medical grand challenges. Her current research interest is in trustworthy medical AI and computational pathology.
URL:https://www.pathologynews.com/event/tia-centre-seminar-series-pathology-foundation-models-for-text-prompted-segmentation-and-precision-oncology/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/png:https://www.pathologynews.com/wp-content/uploads/2026/06/TIA-Centre-Seminar-Series-–-Pathology-Foundation-Models-for-Text-prompted-Segmentation-and-Precision-Oncology-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260629T150000
DTEND;TZID=Europe/London:20260629T160000
DTSTAMP:20260826T183559
CREATED:20260612T080745Z
LAST-MODIFIED:20260612T080745Z
UID:100122112-1782745200-1782748800@www.pathologynews.com
SUMMARY:Pathologist and AI: A Collaboration in Practice
DESCRIPTION:0000Days00Hrs00Min00SecThis webinar will begin at 4:00 pm CEST\, 5:00 pm EEST\, 10:00 am EDT\, 3:00 pm BST \nEven the most accurate AI models only fulfill their full potential when they fit seamlessly into a pathologist’s daily practice. That’s why we explore the collaboration of the pathologist and the AI in the upcoming webinar. The conversation around AI in pathology fixates on the algorithm — but the real difference is made in how the pathologist and the AI work together. \nDuring this session\, Pathologist and Aiforia’s Medical Director\, Richard Doughty\, will discuss: \n\nBetter together: why the AI–pathologist collaboration matters more than the AI itself\nAI and pathologists\, side by side — see how it’s done\nReal labs\, real results — how AI is being used today\, with practical examples from real-world sites\nA live case\, worked in real time\n\nThis webinar will give a clear\, practical view of what good AI–pathologist collaboration actually looks like. \nRegister NowSpeakers\n\nRichard Doughty\, DVM\, MD\, MSc\, Medical Director\, Aiforia Technologies \n\n\n\nConsulting pathologist at Oslo University Hospital\nMedical doctor and specialist in pathology with extensive diagnostic experience.\nQualified veterinarian with pathology expertise in pharmaceutical research and development.\n\n\n\n\nEmilia Lönnberg\, Commercial Product Manager\, Aiforia Technologies \n\n\n\nHas worked at Aiforia for 4 years\nMSc in life science technologies from Aalto University\, major in human neuroscience
URL:https://www.pathologynews.com/event/pathologist-and-ai-a-collaboration-in-practice/
LOCATION:Online
CATEGORIES:Live Online Webinar
ATTACH;FMTTYPE=image/jpeg:https://www.pathologynews.com/wp-content/uploads/2026/06/Pathologist-and-AI-A-Collaboration-in-Practice.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20260630T150000
DTEND;TZID=Europe/London:20260630T160000
DTSTAMP:20260826T183559
CREATED:20260528T090917Z
LAST-MODIFIED:20260528T090917Z
UID:100121779-1782831600-1782835200@www.pathologynews.com
SUMMARY:NPIC Digital Pathology Webinar Series - Innovation into Practice - From Research to Real-world Impact: AI and Innovation at NPIC.
DESCRIPTION:0000Days00Hrs00Min00SecThe National Pathology Imaging Co-Operative (NPIC) continues an exciting new series of free educational webinars on digital pathology topics.​​ \n\nLearn first-hand about hot topics in clinical digital reporting\, the digital laboratory\, IT and informatics and get a chance to pose your questions to the experts!​\nSuitable for pathologists\, biomedical scientists\, informatics and IT professionals\, managers and industry representatives.​\n\n​In this session: \n\nDiscover advances in research and innovation in digital pathology and AI.\nFind out more about NPIC’s multi-scanner research facility and the AI-FORGE platform.\nGain insights into supporting collaboration\, enabling real-world research\, and building the foundations for the future of AI-enabled pathology.\n\nRegister NowPresenters\nDr Daljeet Bansal\nNPIC Operations Director\n\nDr Matthew Humphries\nNPIC Head of Research\n\n\nDr Bethany Williams\nNPIC Knowledge and Skills Lead
URL:https://www.pathologynews.com/event/npic-digital-pathology-webinar-series-innovation-into-practice-from-research-to-real-world-impact-ai-and-innovation-at-npic/
LOCATION:Online
CATEGORIES:Live Online Webinar
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