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 …

[PDF][PDF] Adaptive dynamic dipper throated optimization for feature selection in medical data

G Atteia, ESM El-kenawy, NA Samee… - … Materials & Continua, 2023 - cdn.techscience.cn
The rapid population growth results in a crucial problem in the early detection of diseases in
medical research. Among all the cancers unveiled, breast cancer is considered the second …

Images data practices for semantic segmentation of breast cancer using deep neural network

L Ahmed, MM Iqbal, H Aldabbas, S Khalid… - Journal of Ambient …, 2023 - Springer
Image data in healthcare is playing a vital role. Medical data records are increasing rapidly,
which is beneficial and detrimental at the same time. Large Image dataset are difficult to …

Breast cancer segmentation from thermal images based on chaotic salp swarm algorithm

A Ibrahim, S Mohammed, HA Ali, SE Hussein - IEEE Access, 2020 - ieeexplore.ieee.org
Breast cancer is one of the most common types of cancer and early detection can
significantly decrease the associated mortality rate. Different kinds of segmentation methods …

Breast cancer detection and classification using thermography: a review

A Ibrahim, S Mohammed, HA Ali - The International Conference on …, 2018 - Springer
Cancer is considered as the leading cause of death among people. The cancer is generated
from uncontrolled growth for cells to collect them together to construct tumor. One of these …

Computed tomography (CT) image quality enhancement via a uniform framework integrating noise estimation and super-resolution networks

J Chi, Y Zhang, X Yu, Y Wang, C Wu - Sensors, 2019 - mdpi.com
Computed tomography (CT) imaging technology has been widely used to assist medical
diagnosis in recent years. However, noise during the process of imaging, and data …

[PDF][PDF] A review and computational analysis of breast cancer using different machine learning techniques

V Nemade, S Pathak, AK Dubey… - Int J Emerg Technol Adv …, 2022 - researchgate.net
Breast cancer is found to be prime cause of women death in the current era. It is mainly due
to the late detection of the disease. Artificial intelligence and machine learning plays an …

Analysis of expert system for early diagnosis of disorders during pregnancy using the forward chaining method

B Basiroh, P Priyatno, SW Kareem… - International Journal of …, 2021 - ijair.id
Nowadays technological developments are increasingly having a positive influence on the
development of human life, including in the health sector. One of them is an expert system …

High-Level Hessian-Based Image Processing with the Frangi Neuron

T Hachaj, M Piekarczyk - Electronics, 2023 - mdpi.com
The Frangi neuron proposed in this work is a complex element that allows high-level
Hessian-based image processing. Its adaptive parameters (weights) can be trained using a …

A novel pulmonary nodule detection model based on multi-step cascaded networks

J Chi, S Zhang, X Yu, C Wu, Y Jiang - Sensors, 2020 - mdpi.com
Pulmonary nodule detection in chest computed tomography (CT) is of great significance for
the early diagnosis of lung cancer. Therefore, it has attracted more and more researchers to …