Involvement of machine learning for breast cancer image classification: a survey

AA Nahid, Y Kong - Computational and mathematical methods …, 2017 - Wiley Online Library
Breast cancer is one of the largest causes of women's death in the world today. Advance
engineering of natural image classification techniques and Artificial Intelligence methods …

A hybrid approach based on multiple eigenvalues selection (MES) for the automated grading of a brain tumor using MRI

ZA Al-Saffar, T Yildirim - Computer methods and programs in biomedicine, 2021 - Elsevier
Background and objective: The manual segmentation, identification, and classification of
brain tumor using magnetic resonance (MR) images are essential for making a correct …

[PDF][PDF] Histopathological breast-image classification with restricted Boltzmann machine along with backpropagation

AA Nahid, A Mikaelian, Y Kong - Biomedical Research, 2018 - researchgate.net
Deaths due to cancer have increased rapidly in recent years. Among all the cancer
diseases, breast cancer causes many deaths in women. A digital medical photography …

Multi-feature deep information bottleneck network for breast cancer classification in contrast enhanced spectral mammography

J Song, Y Zheng, J Wang, MZ Ullah, X Li, Z Zou… - Pattern Recognition, 2022 - Elsevier
There is considerable variation in the size, shape and location of tumours, which makes it
challenging for radiologists to diagnose breast cancer. Automated diagnosis of breast …

An automated mammogram classification system using modified support vector machine

AA Kayode, NO Akande, AA Adegun… - … Devices: Evidence and …, 2019 - Taylor & Francis
Purpose Breast cancer remains a serious public health problem that results in the loss of
lives among women. However, early detection of its signs increases treatment options and …

[PDF][PDF] Feature selection mammogram based on breast cancer mining

LC Shofwatul'Uyun - International Journal of Electrical and Computer …, 2018 - academia.edu
The very dense breast of mammogram image makes the Radiologists often have difficulties
in interpreting the mammography objectively and accurately. One of the key success factors …

Diagnosis of anomalies based on hybrid features extraction in thyroid images

M Tasnimi, HR Ghaffari - Multimedia Tools and Applications, 2023 - Springer
Diagnosing benign and malignant glands in thyroid ultrasound images is considered a
challenging issue. Recently, deep learning techniques have significantly resulted in …

A Machine Learning Approach for Enhanced Security Using Blockchain in Finance Auditing Services

MS Banu, N Parveen, R Gayathri… - 2024 15th …, 2024 - ieeexplore.ieee.org
In financial auditing services, which is constantly evolving, it is of the utmost importance to
establish stringent security protocols. Since the financial sector is increasingly being …

Performance comparison of ANN-BP, ELM for MRI pancreas image classification

BA Devi, MP Rajasekaran - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Magnetic resonance imaging (MRI) is a modern way of detecting tumour in medical field.
The convenience of MRI is soft tissue contrast and non invasiveness. Inconvenience of MRI …

Investigations of shallow and deep learning algorithms for tumor detection

S Dhivya, RJ Anjali, S Mohanavalli… - 2020 IEEE …, 2020 - ieeexplore.ieee.org
With the increasing ability of the computer aided detection and diagnosis system, the
exploration on the tumors have attained a breakthrough by decreasing the mortality rate …