Transfer learning in breast cancer diagnoses via ultrasound imaging

G Ayana, K Dese, S Choe - Cancers, 2021 - mdpi.com
Simple Summary Transfer learning plays a major role in medical image analyses; however,
obtaining adequate training image datasets for machine learning algorithms can be …

Breast cancer in Asia: incidence, mortality, early detection, mammography programs, and risk-based screening initiatives

YX Lim, ZL Lim, PJ Ho, J Li - Cancers, 2022 - mdpi.com
Simple Summary Nearly all breast cancer patients survive for more than five years when the
tumor is found early and in the localized stage. Regular clinical breast examinations …

Feasibility of breast cancer detection through a convolutional neural network in mammographs

FM Ahmed, BS MOHAMMED - Tamjeed Journal of Healthcare …, 2023 - tamjeedpub.com
In the Iraq female samples, the malignant neoplasm type with the highest mortality rate is
breast cancer. When the disease is detected early, the success rate is higher, resulting in …

Deep learning cascaded feature selection framework for breast cancer classification: Hybrid CNN with univariate-based approach

NA Samee, G Atteia, S Meshoul, MA Al-antari… - Mathematics, 2022 - mdpi.com
With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …

[HTML][HTML] Trends in breast cancer incidence in Iraq during the period 2000-2019

MMY Al-Hashimi - Asian Pacific journal of cancer prevention …, 2021 - ncbi.nlm.nih.gov
Background: Breast cancer is the most common cancer among women around the world.
Objective: This study aims to explore the time trends in the incidence of breast cancer in Iraq …

ETECADx: Ensemble self-attention transformer encoder for breast cancer diagnosis using full-field digital X-ray breast images

AM Al-Hejri, RM Al-Tam, M Fazea, AH Sable, S Lee… - Diagnostics, 2022 - mdpi.com
Early detection of breast cancer is an essential procedure to reduce the mortality rate among
women. In this paper, a new AI-based computer-aided diagnosis (CAD) framework called …

[PDF][PDF] Classification of breast cancer images using new transfer learning techniques

AA Mukhlif, B Al-Khateeb, M Mohammed - Iraqi Journal For Computer …, 2023 - iasj.net
Breast cancer is one of the most common types of cancer among women, which requires
building smart systems to help doctors and early detection of cancer. Deep learning …

Oncolytic newcastle disease virus Co-delivered with modified PLGA nanoparticles encapsulating temozolomide against glioblastoma cells: Developing an effective …

ZA Kadhim, GM Sulaiman, AM Al-Shammari, RA Khan… - Molecules, 2022 - mdpi.com
Glioblastoma multiforme (GBM) is considered to be one of the most serious version of
primary malignant tumors. Temozolomide (TMZ), an anti-cancer drug, is the most common …

Breast cancer images Classification using a new transfer learning technique

MA Mohammed, AA Mukhlif… - Iraqi Journal for …, 2023 - ijcsm.researchcommons.org
Breast cancer is one of the most common types of cancer among women, which requires
building smart systems to help doctors and early detection of cancer. Deep learning …

MfdcModel: a novel classification model for classification of benign and malignant breast tumors in ultrasound images

W Liu, M Guo, P Liu, Y Du - Electronics, 2022 - mdpi.com
Automatic classification of benign and malignant breast ultrasound images is an important
and challenging task to improve the efficiency and accuracy of clinical diagnosis of breast …