Improved DeTraC Binary Coyote Net‐Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole‐Slide Pathological Images

These findings underscore the effectiveness of ImDeTraC-BCNet-MIL in enhancing the early detection of lymph node metastasis in breast cancer.

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Publication Details

Journal
International Journal of Medical Robotics and Computer Assisted Surgery
Published
2024-11-15
DOI
https://doi.org/10.1002/rcs.70009
Citations
1
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
0.35
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article

Improved DeTraC Binary Coyote Net‐Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole‐Slide Pathological Images

R. Sarath Kumar, R. Padmapriya, M. Ramkumar, S. Balu Mahandiran
1 citations
International Journal of Medical Robotics and Computer Assisted Surgery
AI in cancer detection
0.35
article

Improved DeTraC Binary Coyote Net‐Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole‐Slide Pathological Images

R. Sarath Kumar, R. Padmapriya, M. Ramkumar, S. Balu Mahandiran
article en
1 citations

Abstract

These findings underscore the effectiveness of ImDeTraC-BCNet-MIL in enhancing the early detection of lymph node metastasis in breast cancer.

International Journal of Medical Robotics and Computer Assisted SurgeryVol. 20(6)
Sri Aurobindo Institute of Technology (IN)
Good health and well-being
Openalex Percentile: Top 32%
AI in cancer detection
0.35
DOIOpen Access PDFOpenAlex
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Improved DeTraC Binary Coyote Net‐Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole‐Slide Pathological Images — R. Sarath Kumar, R. Padmapriya, et al. · International Journal of Medical Robotics and Computer Assisted Surgery (2024) | TGRS Research Map | TGRS