Presentation Slides [For attendees of the Digital Pathology Congress only] NB:
You will see that not all the presenters from the
conference are listed below. This is where the
company or speaker have not given permission for
release. This is usually due to corporate rules
or because there was unpublished material in the
presentation. In the case of the latter, we take
the view that it is better to have exclusive
presentations on the day, given before official
publication, than to restrict the content of the
conference by insisting on releasing such data in
slide form, regardless of sensitivity or readiness for
external examination. We hope you feel the same
way.
If you were a speaker and have not yet responded to our request for confirmation, please email scott@globalengage.co.uk to let us know if we can release your slides as a PDF. If there are issues with release, let me know if we need to remove your name from the page or whether there are smaller issues and we can share a revised version of the slides. These slides are provided as a courtesy by the authors, who retain copyright. This is not a publication and slides may be withdrawn at any time at the authors request. |
AI FOR IMAGE ANALYSIS
ANIL PARWANI; Professor of Pathology and Biomedical Informatics, Vice-Chair of Anatomic Pathology, Wexner Medical Center, Ohio State University Breaking the barriers: Whole Slide Imaging for Primary Diagnosis and Artificial Imaging Applications THOMAS FUCHS; Associate Professor, Computational Pathology, Memorial Sloan Kettering Cancer Center; Weill Cornell Medicine What Does It Take to Build a Petabyte Scale AI? ** Awaiting Permission to Release ** JOEL SALTZ; Cherith Professor and Founding Chair, Department of Biomedical Informatics, Stony Brook University Whole Slide Imaging and High-End Computing Come Full Circle DAVID WEST; CEO, Proscia Dr. Strangelove or: How I Learned to Stop Worrying and Love the Machine ULYSSES BALIS; Professor of Pathology, Director, Division of Pathology Informatics & Computational Pathology Laboratory Section, Michigan Medicine, University of Michigan A High-Performance Machine Learning Model System for Automated Segmentation, Classification and Differential Diagnosis Generation from Whole Slide Image Subject Matter ** Awaiting Permission to Release ** GERARDO FERNANDEZ; Associate Professor, Department of Pathology, Medical Director, Center for Computational and Systems Pathology, Icahn School of Medicine at Mount Sinai & The Mount Sinai Hospital Artificial intelligence methods for grading human cancer ** Awaiting Permission to Release ** PETER CAIE; Senior Research Fellow, University of St Andrews, UK Towards Precision Pathology through Automated image Analysis and Machine Learning ** Awaiting Permission to Release ** ERIC WIRCH; Chief Technology Officer and Managing Director, Corista Migrating algorithms beyond the development sandbox COMPUTATIONAL PATHOLOGY & AI
JOHN TOMASZEWSKI; SUNY Distinguished Professor, Peter A. Nickerson Professor and Chair, Department of Pathology and Anatomical Science, University at Buffalo, State University of New York Traditional AI Approaches to Computational Histopathology GUSTAVO KUNDE ROHDE; Associate Professor, Department of Biomedical Engineering, Department of Electrical and Computer Engineering, University of Virginia Interpretable discriminative modeling of cellular phenotypes for digital pathology GEORGE LEE; Digital Pathology Informatics Lead / Data Scientist, Translational Medicine, Bristol-Myers Squibb Applications of Artificial Intelligence for Immuno-oncology and Precision Medicine MICHAEL SURACE; Scientist, MedImmune Validation of multiplex immunofluorescence panels using multispectral microscopy for immune-profiling of formalinfixed and paraffin-embedded human tumor tissues ** Awaiting Permission to Release ** BEATRICE KNUDSEN; Professor, Biomedical Sciences and Pathology and Laboratory Medicine, Director, Translational Pathology, Cedars Sinai Medical Center Nuclear morphometry and cancer biomarker development ADVANCEMENTS IN IMAGING
RICHARD LEVENSON; Professor and Vice Chair for Strategic Technologies, Department of Pathology and Laboratory Medicine, UC Davis Health, Sacramento, CA Slide-free, real-time histology: cooler than frozens YAIR RIVENSON; Postdoctoral Scholar, Ozcan Nano/Bio Photonics Lab, University of California Los Angeles Deep Learning Microscopy for Enhanced Digital Pathology IMPLEMENTATION & PRACTICALITIES
DRAZEN JUKIC; Dermatopathologist, Georgia Dermatopathology; Associate Professor, Mercer University School of Medicine, Department of Medical Education; Associate Professor, Department of Dermatology, University of Florida; Consultant Pathologist, James A. Haley VA Medical Center, Pathology and Laboratory Medicine Service Implementation of day-to-day digital pathology in the US market JASPER PEETERS; Head of Product Management Digital Pathology Solutions, Philips Digital Pathology Customer survey results -100% digital sites DOUGLAS HARTMAN; Associate Professor of Pathology & Associate Director, Pathology Informatics, University of Pittsburgh Determining how to integrate digital pathology into your lab STEVEN HART; Assistant Professor of Biomedical Informatics, Mayo Clinic Digital Pathology at The Intersection of Big Data, AI, and Genomics Poster Presentations Collation of all abstracts
presented in poster form over the 2 days.
Click Here For The Poster Summary Actual posters approved for release: The
Paradox of Exclusion of the Most Interesting
Futuristic Subjects from
Meeting Programs and Summit Papers Ishita Moghe and Kim Solez, University of Alberta, Edmonton, Alberta, Canada Truthful Promotion of Pathology – Building Nonfictional Models of the World to Train Sentient Artificial Intelligence Ishita Moghe and Kim Solez, MD Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada Quantitative spatial analysis of single or multiplexed biomarkers on whole slide digital pathology images in a hospital-based multi-modality core facility Trevor D. McKee PhD, Jade Bilkey, Mark Zaidi, Sehrish Butt MSc, Abhishek Rawat PhD, Fred Fu MSc, Justin Grant PhD MBA, David A. Jaffray PhD ABMP STTARR Innovation Centre, Toronto, Canada A deep learning-based model of normal histology Tobias Sing1*, ImtiazHossain1*, Holger Hoefling1*, Arno Doelemeyer1, Chandrassegar Saravanan2, Alessandro Piaia1, KunoWuersch1, Vincent Romanet1, Wolfgang Zipfel1, Mike Steeves2, Oliver Turner3*, Pierre Moulin1* 1Novartis Institutes for BioMedicalResearch, Basel, Switzerland; 2Novartis Institutes for BioMedicalResearch, Cambridge, MA, USA; 3Novartis Institutes for BioMedicalResearch, East Hanover, NJ, USA *These authors contributed equally Preliminary studies in the use of the foldscope paper microscope for diagnostic analysis of crystals in urine: issues in the analysis of liquid samples and potential applications in low budget/low tech regions of the world Rebecca Calder 2,4, DPM, MLS(ASCP)CM, Daniel Stevens 3,4, DPM, MLS(ASCP)CM and Zev Leifer, Ph.D. 1 1 Professor of Microbiology and Pathology, New York College of Podiatric Medicine (NYCPM), New York, NY (zleifer@nycpm.edu) 2 Podiatric Resident, MetroWest Medical Center, Framingham, MA (rrcalder21@gmail.com) 3 Podiatric Resident, Good Samaritan Hospital Medical Center, West Islip, NY (danieljstevens2@gmail.com) 4 Work done while undergraduate student at NYCPM |
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