An integrative machine learning framework for classifying SEER breast cancer

[1]  J. Rueff,et al.  Genetic determinants and absence of breast cancer in Xavante Indians in Sangradouro Reserve, Brazil , 2023, Scientific Reports.

[2]  I. D. L. T. Díez,et al.  Breast Cancer Prediction Using Fine Needle Aspiration Features and Upsampling with Supervised Machine Learning , 2023, Cancers.

[3]  Fanhua Kong,et al.  Prognostic and immune microenvironment analysis of cuproptosis-related LncRNAs in breast cancer , 2023, Functional & Integrative Genomics.

[4]  Hongyi Li,et al.  Application of serum SERS technology based on thermally annealed silver nanoparticle composite substrate in breast cancer , 2023, Photodiagnosis and Photodynamic Therapy.

[5]  A. Haq,et al.  DEBCM: Deep Learning-Based Enhanced Breast Invasive Ductal Carcinoma Classification Model in IoMT Healthcare Systems. , 2022, IEEE journal of biomedical and health informatics.

[6]  A. Haq,et al.  DACBT: deep learning approach for classification of brain tumors using MRI data in IoT healthcare environment , 2022, Scientific Reports.

[7]  I. Soerjomataram,et al.  Current and future burden of breast cancer: Global statistics for 2020 and 2040 , 2022, Breast.

[8]  A. Fay,et al.  Rapid and low-cost liquid biopsy with ATR-FTIR spectroscopy to discriminate the molecular subtypes of breast cancer. , 2022, Talanta.

[9]  S. Nam,et al.  Survival benefit from axillary surgery in patients aged 70 years or older with clinically node-negative breast cancer: A population-based propensity-score matched analysis. , 2022, European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology.

[10]  Salah Ud Din,et al.  A survey of deep learning techniques based Parkinson's disease recognition methods employing clinical data , 2022, Expert Syst. Appl..

[11]  Sergio A. Velastin,et al.  Feature Selection Using Correlation Analysis and Principal Component Analysis for Accurate Breast Cancer Diagnosis , 2021, J. Imaging.

[12]  Safet Krasniqi.  Education and Vocational Training in Kosovo, A Challenge and Objective of the 21st Century , 2021 .

[13]  Jalaluddin Khan,et al.  Detection of Breast Cancer Through Clinical Data Using Supervised and Unsupervised Feature Selection Techniques , 2021, IEEE Access.

[14]  Fengfeng Zhou,et al.  Survival Time Prediction of Breast Cancer Patients Using Feature Selection Algorithm Crystall , 2021, IEEE Access.

[15]  K. Hegde,et al.  Breast Cancer Prediction Analysis using Machine Learning Algorithms , 2020, 2020 International Conference on Communication, Computing and Industry 4.0 (C2I4).

[16]  Mengran Zhou,et al.  RF-PCA: A New Solution for Rapid Identification of Breast Cancer Categorical Data Based on Attribute Selection and Feature Extraction , 2020, Frontiers in Genetics.

[17]  Bouchaib Cherradi,et al.  Classification of Patients with Breast Cancer using Neighbourhood Component Analysis and Supervised Machine Learning Techniques , 2020, 2020 3rd International Conference on Advanced Communication Technologies and Networking (CommNet).

[18]  Jianping Li,et al.  A novel integrated diagnosis method for breast cancer detection , 2020, J. Intell. Fuzzy Syst..

[19]  Hojjat Adeli,et al.  A dynamic ensemble learning algorithm for neural networks , 2019, Neural Computing and Applications.

[20]  Yijing Wang,et al.  Breast Cancer Prediction using Feature Selection and Ensemble Voting , 2019, 2019 International Conference on System Science and Engineering (ICSSE).

[21]  Dhanya R,et al.  A Comparative Study for Breast Cancer Prediction using Machine Learning and Feature Selection , 2019, 2019 International Conference on Intelligent Computing and Control Systems (ICCS).

[22]  D. Ramyachitra,et al.  Fuzzy based algorithms to predict MicroRNA regulated protein interaction pathways and ranking estimation in Arabidopsis thaliana. , 2019, Gene.

[23]  Raymond Y Huang,et al.  Artificial intelligence in cancer imaging: Clinical challenges and applications , 2019, CA: a cancer journal for clinicians.

[24]  Zhang Yi,et al.  Automated diagnosis of breast ultrasonography images using deep neural networks , 2019, Medical Image Anal..

[25]  Tanupriya Choudhury,et al.  Breast Cancer Detection Using Machine Learning Algorithms , 2018, 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS).

[26]  P. Manikandan,et al.  Enhanced Artificial Neural Network for Protein Fold Recognition and Structural Class Prediction , 2018, Gene Reports.

[27]  P Manikandan,et al.  PATSIM: Prediction and analysis of protein sequences using hybrid Knuth-Morris Pratt (KMP) and Boyer-Moore (BM) algorithm. , 2018, Gene.

[28]  Md. Kamrul Hasan,et al.  Prediction of breast cancer using support vector machine and K-Nearest neighbors , 2017, 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC).

[29]  Sudhanshu Kulshrestha,et al.  Machine learning approaches for breast cancer diagnosis and prognosis , 2017, 2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp).

[30]  D. Ramyachitra,et al.  Bacterial Foraging Optimization –Genetic Algorithm for Multiple Sequence Alignment with Multi-Objectives , 2017, Scientific Reports.

[31]  Chinnaiyan Ponnuraja,et al.  Decision tree Classification and Model Evaluation for Breast Cancer Survivability: A Data Mining Approach , 2017 .

[32]  Subrata Kumar Mandal,et al.  Performance Analysis Of Data Mining Algorithms For Breast Cancer Cell Detection Using Naïve Bayes, Logistic Regression and Decision Tree , 2017 .

[33]  Dana Bazazeh,et al.  Comparative study of machine learning algorithms for breast cancer detection and diagnosis , 2016, 2016 5th International Conference on Electronic Devices, Systems and Applications (ICEDSA).

[34]  P. Manikandan,et al.  An Improved Instance Based K-Nearest Neighbor (IIBK) Classification of Imbalanced Datasets with Enhanced Preprocessing , 2016 .

[35]  D. Ramyachitra,et al.  Interval-value Based Particle Swarm Optimization algorithm for cancer-type specific gene selection and sample classification , 2015, Genomics data.

[36]  Halima Bahi,et al.  Data mining approach , 2012 .

[37]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.

[38]  Robert C. Wolpert,et al.  A Review of the , 1985 .