Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
Precision medicine is one of the recent and powerful developments in medical care, which
has the potential to improve the traditional symptom-driven practice of medicine, allowing …
has the potential to improve the traditional symptom-driven practice of medicine, allowing …
Radiological images and machine learning: trends, perspectives, and prospects
The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …
research area that is expected to grow in the next five to ten years. Recent advances in …
Breast cancer detection using extreme learning machine based on feature fusion with CNN deep features
A computer-aided diagnosis (CAD) system based on mammograms enables early breast
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …
cancer detection, diagnosis, and treatment. However, the accuracy of the existing CAD …
Breast cancer segmentation methods: current status and future potentials
Early breast cancer detection is one of the most important issues that need to be addressed
worldwide as it can help increase the survival rate of patients. Mammograms have been …
worldwide as it can help increase the survival rate of patients. Mammograms have been …
Breast cancer: One-stage automated detection, segmentation, and classification of digital mammograms using UNet model based-semantic segmentation
KB Soulami, N Kaabouch, MN Saidi… - … Signal Processing and …, 2021 - Elsevier
Breast cancer is one of the most common cancers in women. It is known as asymptomatic
cancer that presents no noticeable symptoms in its early stage. Thus, regular mammography …
cancer that presents no noticeable symptoms in its early stage. Thus, regular mammography …
Attention dense-u-net for automatic breast mass segmentation in digital mammogram
S Li, M Dong, G Du, X Mu - Ieee Access, 2019 - ieeexplore.ieee.org
Breast mass is one of the most distinctive signs for the diagnosis of breast cancer, and the
accurate segmentation of masses is critical for improving the accuracy of breast cancer …
accurate segmentation of masses is critical for improving the accuracy of breast cancer …
[HTML][HTML] The applications of genetic algorithms in medicine
A great wealth of information is hidden amid medical research data that in some cases
cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature …
cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature …
A novel feature selection framework based on grey wolf optimizer for mammogram image analysis
B Sathiyabhama, SU Kumar, J Jayanthi… - Neural Computing and …, 2021 - Springer
Breast cancer is one of the significant tumor death in women. Computer-aided diagnosis
(CAD) supports the radiologists in recognizing the irregularities in an efficient manner. In this …
(CAD) supports the radiologists in recognizing the irregularities in an efficient manner. In this …
[HTML][HTML] Benign and malignant breast cancer segmentation using optimized region growing technique
S Punitha, A Amuthan, KS Joseph - Future Computing and Informatics …, 2018 - Elsevier
Breast cancer is one of the dreadful diseases that affect women globally. The occurrences of
breast masses in the breast region are the main cause for women to develop a breast …
breast masses in the breast region are the main cause for women to develop a breast …
Image segmentation using computational intelligence techniques
Image segmentation methodology is a part of nearly all computer schemes as a pre-
processing phase to excerpt more meaningful and useful information for analysing the …
processing phase to excerpt more meaningful and useful information for analysing the …