Breast cancer detection using artificial intelligence techniques: A systematic literature review

AB Nassif, MA Talib, Q Nasir, Y Afadar… - Artificial intelligence in …, 2022 - Elsevier
Cancer is one of the most dangerous diseases to humans, and yet no permanent cure has
been developed for it. Breast cancer is one of the most common cancer types. According to …

Deep learning in cancer pathology: a new generation of clinical biomarkers

A Echle, NT Rindtorff, TJ Brinker, T Luedde… - British journal of …, 2021 - nature.com
Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers.
However, the growing number of these complex biomarkers tends to increase the cost and …

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer

J Ogier du Terrail, A Leopold, C Joly, C Béguier… - Nature medicine, 2023 - nature.com
Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic
potential and poor prognosis, and has limited treatment options. The current standard of …

Breast cancer type classification using machine learning

J Wu, C Hicks - Journal of personalized medicine, 2021 - mdpi.com
Background: Breast cancer is a heterogeneous disease defined by molecular types and
subtypes. Advances in genomic research have enabled use of precision medicine in clinical …

Deep learning technology for improving cancer care in society: New directions in cancer imaging driven by artificial intelligence

M Coccia - Technology in Society, 2020 - Elsevier
The goal of this study is to show emerging applications of deep learning technology in
cancer imaging. Deep learning technology is a family of computational methods that allow …

Deep learning based methods for breast cancer diagnosis: a systematic review and future direction

M Nasser, UK Yusof - Diagnostics, 2023 - mdpi.com
Breast cancer is one of the precarious conditions that affect women, and a substantive cure
has not yet been discovered for it. With the advent of Artificial intelligence (AI), recently, deep …

Breast tumor classification using an ensemble machine learning method

AS Assiri, S Nazir, SA Velastin - Journal of Imaging, 2020 - mdpi.com
Breast cancer is the most common cause of death for women worldwide. Thus, the ability of
artificial intelligence systems to detect possible breast cancer is very important. In this paper …

A hybrid machine learning model for timely prediction of breast cancer

S Dalal, EM Onyema, P Kumar… - … Journal of Modeling …, 2023 - World Scientific
Breast cancer is one of the leading causes of untimely deaths among women in various
countries across the world. This can be attributed to many factors including late detection …

Deep learning in breast cancer imaging: A decade of progress and future directions

L Luo, X Wang, Y Lin, X Ma, A Tan… - IEEE Reviews in …, 2024 - ieeexplore.ieee.org
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Optimizing survival analysis of XGBoost for ties to predict disease progression of breast cancer

P Liu, B Fu, SX Yang, L Deng, X Zhong… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Objective: Some excellent prognostic models based on survival analysis methods for breast
cancer have been proposed and extensively validated, which provide an essential means …