Cancer detection and segmentation using machine learning and deep learning techniques: A review

HM Rai - Multimedia Tools and Applications, 2024 - Springer
Cancer is the most fatal diseases in the world which has highest mortality rate as compared
to other type's human diseases. The most common and dangerous types of cancers are lung …

A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics

HM Rai, J Yoo - Journal of Cancer Research and Clinical Oncology, 2023 - Springer
Purpose There are millions of people who lose their life due to several types of fatal
diseases. Cancer is one of the most fatal diseases which may be due to obesity, alcohol …

Enhancing breast cancer detection and classification using advanced multi-model features and ensemble machine learning techniques

MSA Reshan, S Amin, MA Zeb, A Sulaiman… - Life, 2023 - mdpi.com
Breast cancer (BC) is the most common cancer among women, making it essential to have
an accurate and dependable system for diagnosing benign or malignant tumors. It is …

Computational model for breast cancer diagnosis using HFSE framework

D Kumari, PKR Yannam, IN Gohel, MVSS Naidu… - … Signal Processing and …, 2023 - Elsevier
Mammography is one of the imaging modalities used in diagnosing breast cancer at an
earlier stage. Misdiagnosis leads to risks for the patients. Better feature extraction and …

[HTML][HTML] Cryptographic evidence-based cybersecurity for smart healthcare systems

H Szczepaniuk, EK Szczepaniuk - Information Sciences, 2023 - Elsevier
The idea of smart healthcare assumes the implementation of integrated platforms based on
the Internet of Medical Things to improve the quality of medical processes. An indispensable …

A disease diagnosis system for smart healthcare based on fuzzy clustering and battle royale optimization

F Yan, H Huang, W Pedrycz, K Hirota - Applied Soft Computing, 2024 - Elsevier
The ongoing growth of the Internet of Things and machine learning technology have
provided increased motivation for the development of smart healthcare. In this study, a …

Attention-Based Ensemble Network for Effective Breast Cancer Classification over Benchmarks

SM Thwin, SJ Malebary, AW Abulfaraj, HS Park - Technologies, 2024 - mdpi.com
Globally, breast cancer (BC) is considered a major cause of death among women.
Therefore, researchers have used various machine and deep learning-based methods for its …

Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets

HM Rai, J Yoo, SA Moqurrab, S Dashkevych - Measurement, 2023 - Elsevier
Accurate cancer detection and diagnosis are imperative for advancing patient outcomes and
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …

A structured combination of ensemble classifier and filter-based feature selection to improve breast cancer diagnosis

D Zheng, P Tang, D Lu, L Han, S Saberi - Journal of Cancer Research and …, 2023 - Springer
Introduction Advances in technology have led to the emergence of computerized diagnostic
systems as intelligent medical assistants. Machine learning approaches cannot replace …

Lessons from Twenty Years of Quantum Image Processing

F Yan, SE Venegas-Andraca - ACM Transactions on Quantum …, 2024 - dl.acm.org
Quantum image processing (QIMP) was first introduced in 2003, by Venegas-Andraca et al.
at the University of Oxford. This field attempts to overcome the limitations of classical …