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Machine Learning in Pathology Diagnostics with Simagis Live

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Simagis Live Digital Pathology platform employs latest generation of visual recognition technology with Deep Learning bring game changing application to pathology cancer diagnostics

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Machine Learning in Pathology Diagnostics with Simagis Live

  1. 1. SMART IMAGING TECHNOLOGIES web-pathology.net Machine Learning in Digital Pathology
  2. 2. Analyzing Pathology Slides with Machine Learning Methods Machine Learning algorithms learn to recognize images and patterns in the same way humans do – by example, rather than by human- derived “handcrafted features” such as shape, size, brightness etc. Adding Machine Learning methods to image analysis adds number of benefits: • No need to formalize complex “handcrafted features” by user, pathologist can just point to patterns they need to recognize • No dependency on image analysis engineers (almost) • System can be trained on variety of samples to achieve robust recognition • New data samples can be added to model easily to increase accuracy Since 2012, major improvement in visual recognition was achieved with so called deep learning neural networks. Latest generation of Visual Recognition Neural Networks achieve accuracy of recognition of natural objects similar to human observers. This area of technology is experiencing explosive growth. Approach
  3. 3. Solutions Her2 Scoring Nuclear Biomarkers: ER, PR, Ki-67 CD3 / CD8 Biomarker Scoring H&E Patterns (melanoma, IDC)
  4. 4. How It works Turbo Upload Analyze Stains H&E Pattern Analysis: Melanoma, IDC, other H&E Stain Analyze Stain Type Nuclear Biomarker Scoring: ER, PR, Ki-67 Her2 Scoring Breast IHC Panel CD3 / CD8 scoring, other specialty biomarkers Nuclear Stain Other Membrane Stain IHC Stain Generate Results Visualize Results Send notifications HIPPA compliant email to user with results and link to the case  Smart Apps process whole slide automatically on upload and notify user when analysis is completed  Analysis of a slide takes 2-8 minutes depending on application  Analysis is seamlessly integrated with diagnostic workflow Process Results
  5. 5. Extending Applications  Analysis applications can work on independent computing nodes running on local or remote servers  Applications can use cloud-based recognition services via API  Solutions can combine in-house algorithms with third party analysis routines  Application location is transparent to end users, they use single web interface Slide Store Slide Server Simagis Smart App Simagis Digital Pathology Server Local Algorithm Algorithm 2 Third-party server Algorithm 3 API Imaging Data Application Server Results Application Server 2 Web Interface Users Location 2Location 1 Email
  6. 6. Objective scoring of IHC biomarkers Faster screening of tissue patterns, pattern search Instant case reference. Pattern data mining Predictive Analytics, Personalized Cancer Therapy, Integration with cancer knowledge bases Suggestive Diagnosis, Expert Systems Now Future Benefits of Image Analysis for Histopathology
  7. 7. Classified cancer pattern library is a valuable digital asset that can be licensed to other parties to train visual recognition and image analysis algorithms. Visual recognition application can be used to automatically annotate digital pathology slides and link them with the rest of institutional cancer knowledge base. This application can be licensed to third parties to use for the same purposes. Research and Clinical Applications: • Computer-assisted cancer diagnosis with pre-screening, suggestive diagnosis options and contextual links to cancer knowledge libraries (similar cases, experts, research, additional tests etc.) • Data mining and advanced analytics of historic tissue samples for cancer patients with known outcomes with the purpose of building predictive knowledge bases for cancer care and drug discovery. Classified Pattern Library
  8. 8. • Non SQL flexible indexed database architecture allows integrated storage of different data items across multiple locations Distributed Database • Flexible structure allows storing and integrating various data in the single information store • New data can be added to database structure at any time Comprehensive Data • Selection and navigation is possible for any data item in the database • Global search on any data is instant even for millions of items Instant Search and Navigation • Data items can be linked with external data sources and knowledge bases such as diagnostic codes, SNOMED classifications or proprietary knowledge bases Data Linking We provide instant search, navigation and data mining ability across millions of slides Integration
  9. 9. Integration: Information Systems • RESTful API with live examples and templates provide easy integration with third-party applications Easy API • Integration with other medical information systems is available via HL7 Integration Engine (Rhapsody by Orion Health) LIS / EMR Systems • Third party image analysis application can access images and metadata Algorithms • Information in the database can be integrated with other web based knowledge system via standard integration protocols Knowledge Bases Our product includes standard industry data exchange protocols and APIs for integration with any third party application Integration
  10. 10. Over 2000 registered product users on all continents US Consultation Network of over 200 Pathologists with experts in every specialty Clients and Partners

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