Batch Mode Active Learning on the Riemannian Manifold for Automated Scoring of Nuclear Pleomorphism in Breast Cancer-Reference-Cited by-同舟云学术

Batch Mode Active Learning on the Riemannian Manifold for Automated Scoring of Nuclear Pleomorphism in Breast Cancer

Published:2020-03 Issue: Volume:103 Page:101805
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Das Asha,Nair Madhu S.,Peter David S.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference116 articles.

1. International agency for research on cancer. world health organizarion;Stewart;world cancer report 2014,2014

2. Comparison of the prognostic value of Scarff-Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: Major importance of the mitotic count as a component of both grading systems;Genestie;Anticancer Research,1998

3. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long term follow up;Elston;Histopathology,1991

4. Digital imaging in pathology: whole-slide imaging and beyond;Ghaznavi;Annual Review of Pathology: Mechanisms of Disease,2013

5. Computer-derived nuclear ’grade’ and breast cancer prognosis;Wolberg;Analytical and Quantitative Cytology and Histology,1995

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. PatchSorter: a high throughput deep learning digital pathology tool for object labeling;npj Digital Medicine;2024-06-20

2. Applications of Artificial Intelligence in Breast Pathology;ARCH PATHOL LAB MED;2023

3. A deep learning based classifier framework for automated nuclear atypia scoring of breast carcinoma;Engineering Applications of Artificial Intelligence;2023-04

4. Applications of Artificial Intelligence in Breast Pathology;Archives of Pathology & Laboratory Medicine;2023-02-16

5. Machine Learning Techniques for Automated Nuclear Atypia Detection in Histopathology Images: A Review;Inventive Computation and Information Technologies;2023