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AI/ML Digital Pathology 2020 : AI/Machine Learning for Digital Pathology

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Link: https://human-centered.ai/springer-lncs-ai-machine-learning-for-digital-pathology/
 
When N/A
Where LNAI Book project
Submission Deadline Nov 30, 2019
Final Version Due Jan 15, 2020
Categories    AI   machine learning   explainable ai   digital pathology
 

Call For Papers

Papers are sought cross-domain from Artificial Intelligence/Machine Learning for Digital Pathology, including but not limited to (list not yet complete, in no order):

Weakly supervised learning
Multiple Instance Learning
Multi-Classifier Systems
Transparent Machine Learning
Interpretable Machine Learning
Explainable AI (exAI)
Explainability and Causability
Ethical, Social and Legal Aspects of AI
Transfer Learning
Privacy-Preserving Machine Learning
Performance measures
Conditional random fields
Deep Learning approaches
Ontologies and Machine Learning
Interactive Machine Learning
Identification of diagnostic, prognostic and theragnostic biomarkers
Data preprocessing, Data mapping, Data fusion, Data integration, Data mapping
Data provenance and data curation
Biobank-sample and data quality

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