Breast cancer diagnosis and management guided by data augmentation, utilizing an integrated framework of SHAP and random augmentation

Regularly scheduled physical examinations and the detection of breast cancer recurrences

(2023) Ana-Alicia Beltran-Bless et al.   BREAST

Relation between Prognostics Predictor Evaluation Metrics and Local Interpretability SHAP Values

(2022) Marcia L. Baptista et al.   ARTIFICIAL INTELLIGENCE

A new method to forecast multi-time scale load of natural gas based on augmentation data-machine learning model

(2022) Denglong Ma et al.   CHINESE JOURNAL OF CHEMICAL ENGINEERING

Interpretability analysis for thermal sensation machine learning models: An exploration based on the SHAP approach

(2022) Yuren Yang et al.   INDOOR AIR

DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data

(2022) Damien Dablain et al.   IEEE Transactions on Neural Networks and Learning Systems

Effective treatment of imbalanced datasets in health care using modified SMOTE coupled with stacked deep learning algorithms

(2022) A. Mary Sowjanya et al.   Applied Nanoscience

Multi-Classification of Breast Cancer Lesions in Histopathological Images Using DEEP_Pachi: Multiple Self-Attention Head

(2022) Chiagoziem C. Ukwuoma et al.   Diagnostics

Machine learning and data augmentation approach for identification of rare earth element potential in Indiana Coals, USA

(2022) Snehamoy Chatterjee et al.   INTERNATIONAL JOURNAL OF COAL GEOLOGY

Explanations of Machine Learning Models in Repeated Nested Cross-Validation: An Application in Age Prediction Using Brain Complexity Features

(2022) Riccardo Scheda et al.   Applied Sciences-Basel

Exploring different computational approaches for effective diagnosis of breast cancer

(2022) Anuradha. et al.   PROGRESS IN BIOPHYSICS & MOLECULAR BIOLOGY

Explainable machine learning model for liquefaction potential assessment of soils using XGBoost-SHAP

(2022) Kaushik Jas et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Enhancing Detection of Arabic Social Spam Using Data Augmentation and Machine Learning

(2022) Abdullah M. Alkadri et al.   Applied Sciences-Basel

Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations

(2022) Pramudita Satria Palar et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction

(2022) Irfan Ullah et al.   Travel Behaviour and Society

Breast cancer

(2021) Sibylle Loibl et al.   LANCET

Feature selection and classification in breast cancer prediction using IoT and machine learning

(2021) V.Nanda Gopal et al.   MEASUREMENT

An enhanced Predictive heterogeneous ensemble model for breast cancer prediction

(2021) S. Nanglia et al.   Biomedical Signal Processing and Control

FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification

(2021) Sebastián Maldonado et al.   PATTERN RECOGNITION

Automated Machine Learning: Review of the State-of-the-Art and Opportunities for Healthcare

(2020) Jonathan Waring et al.   ARTIFICIAL INTELLIGENCE IN MEDICINE

Early breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up†

(2019) F Cardoso et al.   ANNALS OF ONCOLOGY

Breast Cancer Diagnosis Using Feature Ensemble Learning Based on Stacked Sparse Autoencoders and Softmax Regression

(2019) Vinod Jagannath Kadam et al.   JOURNAL OF MEDICAL SYSTEMS

A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance

(2019) Dina Elreedy et al.   INFORMATION SCIENCES

Clinical Diagnosis and Management of Breast Cancer

(2016) E. S. McDonald et al.   JOURNAL OF NUCLEAR MEDICINE