Breast ultrasound tumour classification: A Machine Learning—Radiomics based approach
Prediction of breast tumour malignancy using ultrasound imaging, is an important step for
early detection of breast cancer. An efficient prediction system can be a great help to …
early detection of breast cancer. An efficient prediction system can be a great help to …
Bayesian optimization based score fusion of linguistic approaches for improving legal document summarization
Due to the lengthy and complex nature of legal documents, automatic summarization has
very high applicability in this domain. Recently, several researchers have proposed …
very high applicability in this domain. Recently, several researchers have proposed …
A CNN-SVM based computer aided diagnosis of breast cancer using histogram K-means segmentation technique
Breast cancer is the second most common prevalent type of cancer found in women around
the world. Early detection and screening of individuals can be beneficial in helping to bring …
the world. Early detection and screening of individuals can be beneficial in helping to bring …
[HTML][HTML] Machine learning techniques for breast cancer diagnosis and treatment: a narrative review
M Sugimoto, S Hikichi, M Takada… - Annals of Breast …, 2023 - abs.amegroups.org
Objective: This narrative review describes the recent developments and applications of
machine learning (ML), a part of artificial intelligence, concerning breast cancer …
machine learning (ML), a part of artificial intelligence, concerning breast cancer …
Achieving highly efficient breast ultrasound tumor classification with deep convolutional neural networks
Ultrasound imaging is one of the common modalities used nowadays during radiological
screening of breast cancer. A novel residual deep convolutional neural network (DCNN) is …
screening of breast cancer. A novel residual deep convolutional neural network (DCNN) is …
Ensemble methods in combination with compartment models for blood glucose level prediction in type 1 diabetes mellitus
Backgroung: Type 1 diabetes is a disease that adversely affects the daily life of a large
percentage of people worldwide. Daily glucose levels regulation and useful advices …
percentage of people worldwide. Daily glucose levels regulation and useful advices …
A novel voting convergent difference neural network for diagnosing breast cancer
Z Zhang, B Chen, S Xu, G Chen, J Xie - Neurocomputing, 2021 - Elsevier
Breast cancer is one of the most frequently occurred cancers for females, and thus
diagnosing breast cancer is very important. Neural dynamic algorithm (NDA) has been …
diagnosing breast cancer is very important. Neural dynamic algorithm (NDA) has been …
Nature-inspired computing in breast cancer research: Overview, perspective, and challenges of the state-of-the-art techniques
A Sahu, KK Ajeeshkumar, MN Peerzada… - Nature-Inspired …, 2022 - Springer
Nature-inspired computing (NIC) is a relatively new concept to design new algorithms for
solving complex problems based on natural phenomenon. It is a stochastic search …
solving complex problems based on natural phenomenon. It is a stochastic search …
Feature fusion based machine learning pipeline to improve breast cancer prediction
Early detection of malignant breast cancer can significantly improve the survival chances of
the involved patients. Analysis of a non-invasive and non-radioactive modality like …
the involved patients. Analysis of a non-invasive and non-radioactive modality like …
Enhancing Prediction Models' Performance for Breast Cancer using SMOTE Technique
Breast cancer (BC) is a critical public health concern, and the development of accurate
prediction models is crucial for early detection. However, predicting BC using imbalanced …
prediction models is crucial for early detection. However, predicting BC using imbalanced …