توضیحات
1-Abstract
2-Introduction
3-Challenges
Challenge #1: Verification of outcome
Challenge #2: Big Data
Challenge #3: Tools for digitalization
Challenge #4: High complexity of histological images
Challenge #5: High dimensionality of pathology diagnostic problems
Challenge #6: Pathologist as the gold standard/ ground truth
Challenge #7: Affordability of computational power and storage space
Challenge #8: Generalizability
4-Opportunities
Opportunity #1: Powerful Modeling
Opportunity #2: Data augmentation for not enough data
Opportunity #3: Visualization
Opportunity #4: Fast assistantship
Opportunity #5: Ability to deal with complex biomarkers
Opportunity #6: Improved Efficiency and Personalized Treatments
Opportunity #7: Time Saving
Opportunity #8: Reduce Errors
5-Summary
چکیده:
As the digital pathology market grows, facilities that rely on digital pathology will start using artificial intelligence (AI) to assist. AI could help health professionals cope with the gigantic quantities of data. However, this advancement creates some challenges and opportunities. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber‐security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field.
منابع:
- Kayla Matthews, Ways Artificial Intelligence Is Transforming Digital Pathology, hitconsultant, 2019
- Anil V. Parwani, Next generation diagnostic pathology : use of digital pathology and artificial intelligence tools to augment a pathological diagnosis
, diagnosticpathology, biomedcentral, 2019
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- Andreas Holzinger, Prof. Dr. Randy Goebel, Prof. Michael Mengel, Heimo Müller, Artificial Intelligence and Machine Learning for Digital Pathology, springerprofessional.de, 2020
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- Ralf Huss, Why and how should digital pathology be implemented into clinical practice?, DIGITAL PATHOLOGY PLACE
- MICHELLE DOTZERT, Integrating Artificial Intelligence with Digital Pathology, Lab Manager, 2020
- Abels E, et al. Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the digital pathology association. J Pathol. 2019;249(3):286–94.
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