ArticleCancers2023
Hyperparameter Optimizer with Deep Learning-Based Decision-Support Systems for Histopathological Breast Cancer Diagnosis.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Prediction of college student psychological state based on deep learning framework combining the improved Whale Optimization Algorithm and LSTM.Scientific reports · 2026Article
- Leveraging medical imaging and deep learning for diagnosis of breast cancer using histopathological images.Scientific reports · 2026Article
- A hybrid learning framework integrating chaotic Niche alpha evolution for student academic performance prediction.Scientific reports · 2026Article
- The role of AI for improved management of breast cancer: Enhanced diagnosis and health disparity mitigation.Computer methods and programs in biomedicine · 2025Review
- Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization.Scientific reports · 2025Article
- Application of multi-feature-based machine learning models to predict neurological outcomes of cardiac arrest.Resuscitation plus · 2024Review
- Enhanced breast cancer diagnosis through integration of computer vision with fusion based joint transfer learning using multi modality medical images.Scientific reports · 2024Article
- Applications of Deep Learning Techniques in Healthcare Systems: A Review.Journal of clinical practice and research · 2024Review
- Predicting gene signature in breast cancer patients with multiple machine learning models.Discover oncology · 2024Article
- Article
- Histopathology in focus: a review on explainable multi-modal approaches for breast cancer diagnosis.Frontiers in medicine · 2024Review
- Enhancing accessibility for improved diagnosis with modified EfficientNetV2-S and cyclic learning rate strategy in women with disabilities and breast cancer.Frontiers in medicine · 2024Article
- Histopathology-based breast cancer prediction using deep learning methods for healthcare applications.Frontiers in oncology · 2024Article
- Usefulness of machine learning and deep learning approaches in screening and early detection of breast cancer.Heliyon · 2023Review
- Deep Learning for Medical Image-Based Cancer Diagnosis.Cancers · 2023Review
- BCDiagnostics (Basel, Switzerland) · 2023Article
- Article
- MSPO: A machine learning hyperparameter optimization method for enhanced breast cancer image classification.Digital healthArticle
- Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Histopathological images are commonly used imaging modalities for breast cancer. As manual analysis of histopathological images is difficult, automated tools utilizing artificial intelligence (AI) and deep learning (DL) methods should be modelled. The recent advancements in DL approaches will be helpful in establishing maximal image classification performance in numerous application zones. This study develops an arithmetic optimization algorithm with deep-learning-based histopathological breast cancer classification (AOADL-HBCC) technique for healthcare decision making. The AOADL-HBCC technique employs noise removal based on median filtering (MF) and a contrast enhancement process. In addition, the presented AOADL-HBCC technique applies an AOA with a SqueezeNet model to derive feature vectors. Finally, a deep belief network (DBN) classifier with an Adamax hyperparameter optimizer is applied for the breast cancer classification process. In order to exhibit the enhanced breast cancer classification results of the AOADL-HBCC methodology, this comparative study states that the AOADL-HBCC technique displays better performance than other recent methodologies, with a maximum accuracy of 96.77%.
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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.