Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset-Reference-Cited by-同舟云学术

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Annotation protocol and crowdsourcing multiple instance learning classification of skin histological images: The CR-AI4SkIN dataset

Published:2023-11 Issue: Volume:145 Page:102686
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

del Amor Rocío^ORCID,Pérez-Cano Jose^ORCID,López-Pérez Miguel^ORCID,Terradez Liria,Aneiros-Fernandez Jose,Morales Sandra,Mateos Javier^ORCID,Molina Rafael^ORCID,Naranjo Valery

Funder

Ministerio de Economía y Competitividad

Government of Valencia

Polytechnic University of Valencia

Gobierno de España Ministerio de Ciencia e Innovación

University of Granada Vice Chancellor's Office of Research and Knowledge Transfer

Government of Spain Ministry of Universities

EU Framework Programme for Research and Innovation Marie Skłodowska-Curie Actions

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference59 articles.

1. Validation of digital pathology imaging for primary histopathological diagnosis;Snead;Histopathology,2016

2. Deep neural network models for computational histopathology: A survey;Srinidhi;Med Image Anal,2021

3. Deep learning in histopathology: The path to the clinic;Van der Laak;Nat Med,2021

4. Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: Evaluating experts, automated methods, and the crowd;Irshad,2014

5. Crowdsourcing for translational research: Analysis of biomarker expression using cancer microarrays;Lawson;Br J Cancer,2017

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