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On Breast Cancer Detection: An Application of Machine Learning
  Algorithms on the Wisconsin Diagnostic Dataset
v1v2v3v4 (latest)

On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

20 November 2017
Abien Fred Agarap
ArXiv (abs)PDFHTML

Papers citing "On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset"

11 / 11 papers shown
Title
Predictive Modeling for Breast Cancer Classification in the Context of
  Bangladeshi Patients: A Supervised Machine Learning Approach with Explainable
  AI
Predictive Modeling for Breast Cancer Classification in the Context of Bangladeshi Patients: A Supervised Machine Learning Approach with Explainable AI
Taminul Islam
Md. Alif Sheakh
Mst. Sazia Tahosin
Most. Hasna Hena
S. Akash
Y. B. Jardan
Gezahign Fentahun Wondmie
Hiba-Allah Nafidi
Mohammed Bourhia
80
55
0
06 Apr 2024
UGGNet: Bridging U-Net and VGG for Advanced Breast Cancer Diagnosis
UGGNet: Bridging U-Net and VGG for Advanced Breast Cancer Diagnosis
Tran Cao Minh
Nguyen Kim Quoc
P. Vinh
Dang Nhu Phu
Vuong Xuan Chi
Ha Minh Tan
116
4
0
06 Jan 2024
Machine Learning Approaches to Predict Breast Cancer: Bangladesh
  Perspective
Machine Learning Approaches to Predict Breast Cancer: Bangladesh Perspective
Taminul Islam
Arindom Kundu
Nazmul Islam Khan
Choyon Chandra Bonik
Flora Akter
Md. Jihadul Islam
53
19
0
30 Jun 2022
Breast Cancer Classification using Deep Learned Features Boosted with
  Handcrafted Features
Breast Cancer Classification using Deep Learned Features Boosted with Handcrafted FeaturesBiomedical Signal Processing and Control (BSPC), 2022
Unaiza Sajid
Rizwan Ahmed Khan
S. M. Shah
Sheeraz Arif
OOD
112
50
0
26 Jun 2022
Efficient Learning of Interpretable Classification Rules
Efficient Learning of Interpretable Classification RulesJournal of Artificial Intelligence Research (JAIR), 2022
Bishwamittra Ghosh
Dmitry Malioutov
Kuldeep S. Meel
144
11
0
14 May 2022
Stabilizing Adversarially Learned One-Class Novelty Detection Using
  Pseudo Anomalies
Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo AnomaliesIEEE Transactions on Image Processing (IEEE TIP), 2022
M. Zaheer
Jin-ha Lee
Arif Mahmood
Marcella Astrid
Seung-Ik Lee
AAML
175
22
0
25 Mar 2022
Artificial Intelligence For Breast Cancer Detection: Trends & Directions
Artificial Intelligence For Breast Cancer Detection: Trends & Directions
S. M. Shah
Rizwan Ahmed Khan
Sheeraz Arif
Unaiza Sajid
OOD
160
78
0
03 Oct 2021
$\text{O}^2$PF: Oversampling via Optimum-Path Forest for Breast Cancer
  Detection
O2\text{O}^2O2PF: Oversampling via Optimum-Path Forest for Breast Cancer Detection
L. A. Passos
D. Jodas
L. C. Ribeiro
Thierry Pinheiro Moreira
João Paulo Papa
66
1
0
14 Jan 2021
Machine Learning Towards Intelligent Systems: Applications, Challenges,
  and Opportunities
Machine Learning Towards Intelligent Systems: Applications, Challenges, and OpportunitiesArtificial Intelligence Review (AIR), 2021
MohammadNoor Injadat
Abdallah Moubayed
Ali Bou Nassif
Abdallah Shami
281
125
0
11 Jan 2021
Data Appraisal Without Data Sharing
Data Appraisal Without Data SharingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Mimee Xu
Laurens van der Maaten
Awni Y. Hannun
TDI
253
6
0
11 Dec 2020
Inception Architecture and Residual Connections in Classification of
  Breast Cancer Histology Images
Inception Architecture and Residual Connections in Classification of Breast Cancer Histology Images
Mohammad Ibrahim Sarker
Hyongsuk Kim
Denis Tarasov
Dinar Akhmetzanov
28
8
0
10 Dec 2019
1