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  4. Cited By
Deep Learning to Improve Breast Cancer Early Detection on Screening
  Mammography

Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

30 August 2017
Li Shen
L. Margolies
J. Rothstein
Eugene Fluder
R. McBride
W. Sieh
    MedIm
ArXivPDFHTML

Papers citing "Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography"

43 / 93 papers shown
Title
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained
  EfficientNet-Based Convolutional Network
Breast Cancer Diagnosis in Two-View Mammography Using End-to-End Trained EfficientNet-Based Convolutional Network
D. Petrini
C. Shimizu
R. A. Roela
G. Valente
M. A. K. Folgueira
Hae Yong Kim
MedIm
14
36
0
01 Oct 2021
An End-to-end Entangled Segmentation and Classification Convolutional
  Neural Network for Periodontitis Stage Grading from Periapical Radiographic
  Images
An End-to-end Entangled Segmentation and Classification Convolutional Neural Network for Periodontitis Stage Grading from Periapical Radiographic Images
Tanjida Kabir
Chun-Teh Lee
J. Nelson
Sally Sheng
Hsiu-Wan Meng
Luyao Chen
Muhammad Walji
Xioaqian Jiang
Shayan Shams
15
12
0
27 Sep 2021
Melatect: A Machine Learning Model Approach For Identifying Malignant
  Melanoma in Skin Growths
Melatect: A Machine Learning Model Approach For Identifying Malignant Melanoma in Skin Growths
Vidushi Meel
Asritha Bodepudi
MedIm
11
3
0
07 Sep 2021
Unsupervised multi-latent space reinforcement learning framework for
  video summarization in ultrasound imaging
Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging
R. P. Mathews
Mahesh Raveendranatha Panicker
A. Hareendranathan
Yale Tung Chen
Jacob L. Jaremko
Brian M. Buchanan
K. Narayan
C. Kesavadas
G. Mathews
6
5
0
03 Sep 2021
Multimodal Breast Lesion Classification Using Cross-Attention Deep
  Networks
Multimodal Breast Lesion Classification Using Cross-Attention Deep Networks
Hung Q. Vo
Pengyu Yuan
T. He
Stephen T. C. Wong
H. Nguyen
11
1
0
21 Aug 2021
Meta-repository of screening mammography classifiers
Meta-repository of screening mammography classifiers
Benjamin Stadnick
Jan Witowski
Vishwaesh Rajiv
Jakub Chledowski
Farah E. Shamout
Kyunghyun Cho
Krzysztof J. Geras
20
11
0
10 Aug 2021
A Real Use Case of Semi-Supervised Learning for Mammogram Classification
  in a Local Clinic of Costa Rica
A Real Use Case of Semi-Supervised Learning for Mammogram Classification in a Local Clinic of Costa Rica
Saul Calderon-Ramirez
Diego Murillo-Hernandez
Kevin Rojas-Salazar
David Elizondo
Shengxiang-Yang
Miguel A. Molina-Cabello
10
14
0
24 Jul 2021
Self-transfer learning via patches: A prostate cancer triage approach
  based on bi-parametric MRI
Self-transfer learning via patches: A prostate cancer triage approach based on bi-parametric MRI
Alvaro Fernandez-Quilez
T. Eftestøl
M. G. Olsen
S. R. Kjosavik
K. Oppedal
MedIm
8
4
0
22 Jul 2021
Memory-aware curriculum federated learning for breast cancer
  classification
Memory-aware curriculum federated learning for breast cancer classification
Amelia Jiménez-Sánchez
Mickael Tardy
M. A. G. Ballester
Diana Mateus
Gemma Piella
OOD
25
85
0
06 Jul 2021
An XAI Approach to Deep Learning Models in the Detection of DCIS
An XAI Approach to Deep Learning Models in the Detection of DCIS
Michele La Ferla
Matthew Montebello
Dylan Seychell
17
3
0
27 Jun 2021
Imperceptible Adversarial Examples for Fake Image Detection
Imperceptible Adversarial Examples for Fake Image Detection
Quanyu Liao
Yuezun Li
Xiaoqiang Guo
Bin Kong
Yingxin Zhu
Jianlei Liu
Zhuqing Jiang
Qi Song
Xi Wu
AAML
93
33
0
03 Jun 2021
Do Feature Attribution Methods Correctly Attribute Features?
Do Feature Attribution Methods Correctly Attribute Features?
Yilun Zhou
Serena Booth
Marco Tulio Ribeiro
J. Shah
FAtt
XAI
22
132
0
27 Apr 2021
Research on the Detection Method of Breast Cancer Deep Convolutional
  Neural Network Based on Computer Aid
Research on the Detection Method of Breast Cancer Deep Convolutional Neural Network Based on Computer Aid
Mengfan Li
12
17
0
23 Apr 2021
Low-Regret Active learning
Low-Regret Active learning
Cenk Baykal
Lucas Liebenwein
Dan Feldman
Daniela Rus
UQCV
18
3
0
06 Apr 2021
Invertible Residual Network with Regularization for Effective Medical
  Image Segmentation
Invertible Residual Network with Regularization for Effective Medical Image Segmentation
Kashu Yamazaki
V. Rathour
T. Hoang Ngan Le
MedIm
39
6
0
16 Mar 2021
Detection and severity classification of COVID-19 in CT images using
  deep learning
Detection and severity classification of COVID-19 in CT images using deep learning
Yazan Qiblawey
Anas Tahir
M. Chowdhury
Amith Khandakar
S. Kiranyaz
Tawsifur Rahman
Nabil Ibtehaz
S. Mahmud
Somaya Al-Madeed
F. Musharavati
8
109
0
15 Feb 2021
Interpretable COVID-19 Chest X-Ray Classification via Orthogonality
  Constraint
Interpretable COVID-19 Chest X-Ray Classification via Orthogonality Constraint
Ella Y. Wang
Anirudh Som
Ankita Shukla
Hongjun Choi
P. Turaga
OOD
38
3
0
02 Feb 2021
Beyond Fine-tuning: Classifying High Resolution Mammograms using
  Function-Preserving Transformations
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
Tao Wei
Angelica I Aviles-Rivero
Shuo Wang
Yuan Huang
F. Gilbert
Carola-Bibiane Schönlieb
C. L. P. Chen
MedIm
18
14
0
20 Jan 2021
Task-driven Self-supervised Bi-channel Networks for Diagnosis of Breast
  Cancers with Mammography
Task-driven Self-supervised Bi-channel Networks for Diagnosis of Breast Cancers with Mammography
Ronglin Gong
Jun Wang
Jun Shi
18
0
0
15 Jan 2021
Machine Learning Towards Intelligent Systems: Applications, Challenges,
  and Opportunities
Machine Learning Towards Intelligent Systems: Applications, Challenges, and Opportunities
MohammadNoor Injadat
Abdallah Moubayed
Ali Bou Nassif
Abdallah Shami
57
98
0
11 Jan 2021
Knowledge Distillation with Adaptive Asymmetric Label Sharpening for
  Semi-supervised Fracture Detection in Chest X-rays
Knowledge Distillation with Adaptive Asymmetric Label Sharpening for Semi-supervised Fracture Detection in Chest X-rays
Yirui Wang
K. Zheng
Chi-Tung Chang
Xiaoyun Zhou
Zhilin Zheng
Lingyun Huang
Jing Xiao
Le Lu
Chien-Hung Liao
S. Miao
20
19
0
30 Dec 2020
Data Appraisal Without Data Sharing
Data Appraisal Without Data Sharing
Mimee Xu
L. V. D. van der Maaten
Awni Y. Hannun
TDI
18
6
0
11 Dec 2020
Deep Convolutional Neural Networks: A survey of the foundations,
  selected improvements, and some current applications
Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications
Lars Lien Ankile
Morgan Feet Heggland
Kjartan Krange
AAML
14
55
0
25 Nov 2020
Boosted EfficientNet: Detection of Lymph Node Metastases in Breast
  Cancer Using Convolutional Neural Network
Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network
Jun Wang
Qianying Liu
Haotian Xie
Zhaogang Yang
Hefeng Zhou
MedIm
6
77
0
10 Oct 2020
Explainable Disease Classification via weakly-supervised segmentation
Explainable Disease Classification via weakly-supervised segmentation
A. Joshi
Gaurav Mishra
J. Sivaswamy
17
4
0
24 Aug 2020
Dual Convolutional Neural Networks for Breast Mass Segmentation and
  Diagnosis in Mammography
Dual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography
Heyi Li
Dongdong Chen
W. Nailon
Mike E. Davies
Dave Laurenson
8
51
0
07 Aug 2020
AMITE: A Novel Polynomial Expansion for Analyzing Neural Network
  Nonlinearities
AMITE: A Novel Polynomial Expansion for Analyzing Neural Network Nonlinearities
Mauro J. Sanchirico
Xun Jiao
Chandrasekhar Nataraj
17
3
0
13 Jul 2020
Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast
  Cancer Risk Models
Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models
Yue Liu
Hossein Azizpour
Fredrik Strand
Kevin Smith
12
10
0
11 Jul 2020
Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease
  Dependencies and Uncertainty Labels
Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease Dependencies and Uncertainty Labels
Hieu H. Pham
T. Le
Dat Ngo
Dat Q. Tran
H. Nguyen
12
163
0
25 May 2020
CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19
  Using CT Image
CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
T. Javaheri
Morteza Homayounfar
Zohreh Amoozgar
R. Reiazi
F. Homayounieh
...
Guanglan Zhang
L. Chitkushev
B. Haibe-Kains
R. Malekzadeh
Reza Rawassizadeh
17
51
0
06 May 2020
A Two-Stage Multiple Instance Learning Framework for the Detection of
  Breast Cancer in Mammograms
A Two-Stage Multiple Instance Learning Framework for the Detection of Breast Cancer in Mammograms
Chandra K. Sarath
A. Chakravarty
N. Ghosh
Tandra Sarkar
Ramanathan Sethuraman
Debdoot Sheet
MedIm
6
11
0
24 Apr 2020
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised
  Framework for Medical Image Classification
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification
Marianne de Vriendt
P. Sellars
Angelica I Aviles-Rivero
GNN
9
0
0
13 Mar 2020
Joint 2D-3D Breast Cancer Classification
Joint 2D-3D Breast Cancer Classification
G. Liang
Xiaoqin Wang
Yu Zhang
Xin Xing
Hunter Blanton
Tawfiq Salem
Nathan Jacobs
15
39
0
27 Feb 2020
An interpretable classifier for high-resolution breast cancer screening
  images utilizing weakly supervised localization
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization
Yiqiu Shen
Nan Wu
Jason Phang
Jungkyu Park
Kangning Liu
...
Laura Heacock
S. G. Kim
Linda Moy
Kyunghyun Cho
Krzysztof J. Geras
19
168
0
13 Feb 2020
Zoom in to where it matters: a hierarchical graph based model for
  mammogram analysis
Zoom in to where it matters: a hierarchical graph based model for mammogram analysis
Hao Du
Jiashi Feng
Mengling Feng
14
13
0
16 Dec 2019
Interpreting chest X-rays via CNNs that exploit hierarchical disease
  dependencies and uncertainty labels
Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels
Hieu H. Pham
T. Le
Dat Q. Tran
Dat Ngo
H. Nguyen
14
32
0
15 Nov 2019
Deep Evidential Regression
Deep Evidential Regression
Alexander Amini
Wilko Schwarting
A. Soleimany
Daniela Rus
EDL
PER
BDL
UD
UQCV
17
417
0
07 Oct 2019
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer
  Screening
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
Nan Wu
Jason Phang
Jungkyu Park
Yiqiu Shen
Zhe Huang
...
S. G. Kim
Laura Heacock
Linda Moy
Kyunghyun Cho
Krzysztof J. Geras
MedIm
10
492
0
20 Mar 2019
Adversarial Augmentation for Enhancing Classification of Mammography
  Images
Adversarial Augmentation for Enhancing Classification of Mammography Images
Lukás Jendele
Ondrej Skopek
Anton S. Becker
E. Konukoglu
MedIm
GAN
20
5
0
20 Feb 2019
Conditional Infilling GANs for Data Augmentation in Mammogram
  Classification
Conditional Infilling GANs for Data Augmentation in Mammogram Classification
E. Wu
K. Wu
David D. Cox
William Lotter
MedIm
19
134
0
21 Jul 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition
This Looks Like That: Deep Learning for Interpretable Image Recognition
Chaofan Chen
Oscar Li
Chaofan Tao
A. Barnett
Jonathan Su
Cynthia Rudin
24
1,155
0
27 Jun 2018
DeepMiner: Discovering Interpretable Representations for Mammogram
  Classification and Explanation
DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation
Jimmy Wu
Bolei Zhou
D. Peck
S. Hsieh
V. Dialani
Lester W. Mackey
Genevieve Patterson
FAtt
MedIm
6
24
0
31 May 2018
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Bayesian Uncertainty Estimation for Batch Normalized Deep Networks
Mattias Teye
Hossein Azizpour
Kevin Smith
BDL
UQCV
20
239
0
18 Feb 2018
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