Prognostic Stratification of Low vs. High-Risk Breast Cancer Patients via Master Regulator Analysis (OncoMasTR) Using Digital Pathology and Image Analysis
Computer Vision & Machine Learning in Digital Neuropathology
Developing automated QC tools to enrich histopathology data and to assemble targeted datasets that enable ground-breaking pathology discoveries
Towards Open Pathology with HALO AP®: A Diagnostic Digital Pathology Platform
Deep Learning Workflow for Scalable Detection of Tau Inclusions in Digital Pathology
Where Tissue Meets Tech: The Clinical Benefits and ROI in Digital Pathology Start Here
Standardisation of surgical pathology annotation libraries – a proposal
Computational models to assess tissue micro-environmente
Successful deployment of AI for primary diagnosis of prostate biopsies in BCUHB Wales
Pathologists with their Heads in the Cloud; Moving Diagnoses Online
Metric-Based Validation of WSI Scanner Colour and Quantitative Standardisation for Pathologists and AI
Digital Pathology: There and Back Again
Digital Pathology and Artificial Intelligence for Clinical Diagnostics: Value Proposition and Challenges of Full Scale Implementation
Deep Learning Predicts Breast Cancer Metastasis with Sentinel Lymph Nodes
AI Driven Decision Support and Analytics in Non-Clinical Pathology
A.I. in Prostate Cancer
An Academic Perspective on Digital Pathology with New Ways of Defining Success
Concordance study between digital analysis vs. manual scoring for PD-L1 & CD8
Implementation of digital pathology for routine diagnosis: experience of Rennes University Hospital
Dense mapping of breast cancer tissue components through crowdsourcing
Deep learning in Digital Pathology Powers Cancer Treatment, Research, and Optical Biopsy
Guidelines for Validating Whole Slide Imaging for Diagnostic Purposes: What’s New in 2020?
Leading or Lagging- Is Digital Pathology a Bane or Boon to Pathology Training Programs?
Computational Pathology as a Companion Diagnostic: Implications for Precision Medicine
AI, Digital Pathology and Observer Variability: From Image Search to Building Diagnostic Consensus
Interpretable Discriminative Modelling of Cellular Phenotypes for Digital Pathology
Telepathology – Still the #1 application of Digital Pathology
Kidney Medicine in the Digital Age: Single Cell Sequencing and Artificial Intelligence
How Digitisation Can Improve Pathology Service – the Danish Experience
Nuclear Morphometry and Cancer Biomarker Development
Applications of Artificial Intelligence for Immuno-oncology and Precision Medicine
Dr. Strangelove, or: How I Learned to Stop Worrying and Love the Machine
AI, Digital Pathology and Image Analysis on the Raspberry Pi
Webinars
A.I. in Prostate Cancer
Paige Receives Clinical Approval for AI In Pathology
Digital Pathology Masterclass – Demystifying Digital Pathology Deployment
High Dimensional Spatial Biology: From Discovery to High Throughput Studies
Explore Spatial Biology with LCM Digital Pathology Cloud Research Solution
Bridge Digital and Molecular Pathology
Digital Pathology Educational Program
Routine Use of AI Towards Automating Histopathology Analysis
Poster Presentations
Standing on the Shoulders of Giants – Towards a winning FP9 proposal
Up-converting nanoparticles as a tool for histopathological tissue evaluation with multiplexing and machine learning potential
Convolutional neural network for colonoscopy tissue segmentation and classification
Tumor budding in brightfield immunostained colon sections
On the verge of clinical outcome prediction: humans teaching machines – machines teaching humans
High Proximity Between T cells and PD-L1+ Cells in HPV Negative Oropharyngeal Cancer Predicts Poor Outcome
Single-Cell Sequencing & Artificial Intelligence: Bringing Kidney Transplantation to the Digital Age & Beyond
Deep learning based detection of tumor tissue compartments improves prognostic immunoprofiling in muscle-invasive bladder cancer
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
Distinction of Benign and Malignant Breast Histology Through Deep Learning
Biomarker Colocalization Analysis of a Virtual 12-plex using Discovery Chromogenic Dyes and Tissuealign Co-Registration Software
Multimodal Image Analysis: Relationship Between Pathological Image and Microscopic Ultrasound Image
Truthful Promotion of Pathology – Building Nonfictional Models of the World to Train Sentient Artificial Intelligence
Machine Learning Approach to Tumor Immune Infiltrate Analysis from H&E Images
Automatic Detection of Slides to Rescan for Whole Slide Imaging Scanner
A Deep Learning-based Model of Normal Histology
Toward the Automation of Fluorescence In Situ Hybridization (FISH) Scoring Using a Confocal Whole Slide Image Scanner and Image Analysis Software
Presentation Slides
Digital Pathology & AI for Clinical Diagnostics: Value Proposition & Challenges of Implementation
There and back again
Deep Learning predicts breast cancer metastasis with sentinel lymph nodes
Digital image biobanking for the modern pathology core research lab
Quantitative Image Analysis for Tissue Biomarkers
How regulatory science can fasten innovation in digital pathology and ML/AI
Histology Simplified: Leveraging AI driven, automated workflows to accelerate digital pathology
Quantitative Color: Metric-Based QA for WSI Color and Impact of Standardisation on Digital Pathology and AI
User interface automation of a commercial whole-slide imaging system
Up-Converting NanoParticles as a powerful tool for tissue evaluation
Using Modern Technologies in Digital Pathology to Diagnose Children With Cancer in Malawi From 7,400 Miles Away
Melanoma Diagnosis and Staging using Digital Pathology
Kidney Medicine in the Digital Age: Single-Cell Sequencing & AI
Applications of deep neural networks for of digital pathology (and embryo) image classification
Disease processes by pixel analysis – the new era of digital pathology
An Image Retrieval System for Digital Pathology
Digital Pathology at John Hopkins
Implementation of day-to-day Digital Pathology in the US market
PRS: Co-resident Objective Measure of IHC Stain Performance for Process QC and Diagnostic Aid
Applied Digital Pathology in Colon and Lung Cancer Research
Open and Collaborative Software for Digital Pathology
Digital Pathology – Implementing it in a Leading Cancer Centre
Digital Pathology Customer Survey Results – 100% digital slides
Reports
The Benefits of Computational Pathology
Digital Pathology as a Diagnostic Tool
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