ArticlePeerJ. Computer science2021
BCD-WERT: a novel approach for breast cancer detection using whale optimization based efficient features and extremely randomized tree algorithm.
Article in PeerJ. Computer science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Comprehensive Review on the Optical Micro-Electromechanical Sensors for the Biomedical Application.Frontiers in public health · 2021Pooled it
- A Nomogram for Predicting Cancer-Specific Survival of Osteosarcoma and Ewing's Sarcoma in Children: A SEER Database Analysis.Frontiers in public health · 2022Trial
- A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Hypopharyngeal Squamous Cell Carcinomas: A Population-Based Study.Frontiers in public health · 2021Trial
- Machine learning predicts non-thyroidal illness syndrome (NTIS) occurrence and mortality in sepsis patients.European journal of medical research · 2025Article
- Clinical Characteristics of Adenovirus Pneumonia in Children.Pathogens (Basel, Switzerland) · 2025Article
- Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Hybrid metaheuristic optimization for detecting and diagnosing noncommunicable diseases.Scientific reports · 2025Article
- Enhancing breast cancer prediction through stacking ensemble and deep learning integration.PeerJ. Computer science · 2025Article
- Development and validation of a machine-learning model for predicting postoperative pneumonia in aneurysmal subarachnoid hemorrhage.Neurosurgical review · 2024Article
- Prediction and Detection of Cervical Malignancy Using Machine Learning Models.Asian Pacific journal of cancer prevention : APJCP · 2023Article
- Local-Ternary-Pattern-Based Associated Histogram Equalization Technique for Cervical Cancer Detection.Diagnostics (Basel, Switzerland) · 2023Article
- Cancer detection for small-size and ambiguous tumors based on semantic FPN and transformer.PloS one · 2023Article
- Development and validation of a nomogram to predict cancer-specific survival with unresected cholangiocarcinoma undergoing external radiotherapy.Frontiers in public health · 2023Article
- Privacy Preserved Cervical Cancer Detection Using Convolutional Neural Networks Applied to Pap Smear Images.Computational and mathematical methods in medicine · 2023Article
- Feature Generalization for Breast Cancer Detection in Histopathological Images.Interdisciplinary sciences, computational life sciences · 2022Article
- Bio-Imaging-Based Machine Learning Algorithm for Breast Cancer Detection.Diagnostics (Basel, Switzerland) · 2022Article
- An efficient computer vision-based approach for acute lymphoblastic leukemia prediction.Frontiers in computational neuroscience · 2022Article
- Application of Machine Learning in Intelligent Medical Image Diagnosis and Construction of Intelligent Service Process.Computational intelligence and neuroscience · 2022Review
- A Neural Network and Optimization Based Lung Cancer Detection System in CT Images.Frontiers in public health · 2022Article
- Breast Tumor Detection and Classification in Mammogram Images Using Modified YOLOv5 Network.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is one of the leading causes of death in the current age. It often results in subpar living conditions for a patient as they have to go through expensive and painful treatments to fight this cancer. One in eight women all over the world is affected by this disease. Almost half a million women annually do not survive this fight and die from this disease. Machine learning algorithms have proven to outperform all existing solutions for the prediction of breast cancer using models built on the previously available data. In this paper, a novel approach named BCD-WERT is proposed that utilizes the Extremely Randomized Tree and Whale Optimization Algorithm (WOA) for efficient feature selection and classification. WOA reduces the dimensionality of the dataset and extracts the relevant features for accurate classification. Experimental results on state-of-the-art comprehensive dataset demonstrated improved performance in comparison with eight other machine learning algorithms: Support Vector Machine (SVM), Random Forest, Kernel Support Vector Machine, Decision Tree, Logistic Regression, Stochastic Gradient Descent, Gaussian Naive Bayes and k-Nearest Neighbor. BCD-WERT outperformed all with the highest accuracy rate of 99.30% followed by SVM achieving 98.60% accuracy. Experimental results also reveal the effectiveness of feature selection techniques in improving prediction accuracy.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.