Machine learning in breast cancer imaging: a review on data, models and methods

MAVM Grinet, AIR Gouveia… - Computer Methods in …, 2024 - Taylor & Francis
Medical imaging research has experienced significant growth over the past decade,
particularly in the fields of computer vision and pattern recognition. Computational …

Machine-learning methods in detecting breast cancer and related therapeutic issues: a review

A Jafari - Computer Methods in Biomechanics and Biomedical …, 2024 - Taylor & Francis
ABSTRACT In 2020, the World Health Organization reported that breast cancer resulted in
the deaths of 685,000 people worldwide, with 2.3 million women diagnosed with the …

Segmentation of pectoral muscle from mammograms using U-Net having densely connected convolutional layers

SD Deb, RK Jha - Multimedia Tools and Applications, 2024 - Springer
Segmentation of the pectoral muscle is one of the most fundamental steps in developing a
Computer-Aided Diagnosis (CAD) System. Considering the presence of various artifacts and …

Inter-software reliability and agreement for follicular and luteal morphometric and echotextural ultrasonographic parameters in beef cattle

CA Pinzón-Osorio, MA Machado… - Animal Reproduction …, 2024 - Elsevier
This study aimed to compare the inter-software and inter-observer reliability and agreement
for the assessment of follicular and luteal morphometry and echotexture parameters in beef …

Comparing four algorithms in predicting the risk of driving under the influence of alcohol among individuals with alcohol use disorder

HJ Chiu, CK Sun, YL Liu, YR Sue, PY Yeh - Current Psychology, 2024 - Springer
Driving under the influence of alcohol (DUIA) is closely associated with alcohol use disorder
(AUD) because of significant impacts of alcoholism on brain functions related to response …

A novel decision fusion approach for sale price prediction using Elastic Net and MOPSO

AE Chaleshtori - arXiv preprint arXiv:2403.20033, 2024 - arxiv.org
Price prediction algorithms propose prices for every product or service according to market
trends, projected demand, and other characteristics, including government rules …

Classification of Cancer Microarray Data Based on Deep Learning: A Review

J Fadhil, AM Abdulazeez - Indonesian Journal of Computer Science, 2024 - 3.8.6.95
This review article delves into applying deep learning methodologies in conjunction with
microarray data for cancer classification. The study provides a comprehensive overview of …

Enhancing Breast Cancer Detection in Mammography Using Firefly Algorithm-Based Image Enhancement Techniques

R Gudur, P Pati, C Bhatt, S Kukreti - International Journal of Intelligent …, 2024 - ijisae.org
Early identification is essential for effective treatment and improved patient outcomes in
breast cancer, which continues to be a prevalent worldwide health concern. Widely used as …

A Progressive UNDML Framework Model for Breast Cancer Diagnosis and Classification

G Meenalochini, DA Guka, R Sivasakthivel… - Data and …, 2024 - dm.saludcyt.ar
According to recent research, it is studied that the second most common cause of death for
women worldwide is breast cancer. Since it can be incredibly difficult to determine the true …

[PDF][PDF] Journal Homepage:-www. journalijar. com

RN Mohalder, MA Hossain, N Hossain - researchgate.net
For a long time, various ML algorithms have been effectively used for creating predictive
casts from the dataset. ML algorithms and data mining tools in expert-based disciplines are …