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 …

Artificial intelligence in breast imaging: potentials and limitations

EB Mendelson - American Journal of Roentgenology, 2019 - Am Roentgen Ray Soc
OBJECTIVE. The purpose of this article is to discuss potential applications of artificial
intelligence (AI) in breast imaging and limitations that may slow or prevent its adoption …

Deep learning and machine learning with grid search to predict later occurrence of breast Cancer metastasis using clinical data

X Jiang, C Xu - Journal of clinical medicine, 2022 - mdpi.com
Background: It is important to be able to predict, for each individual patient, the likelihood of
later metastatic occurrence, because the prediction can guide treatment plans tailored to a …

Breast cancer detection using convolutional neural networks for mammogram imaging system

YJ Tan, KS Sim, FF Ting - 2017 International Conference on …, 2017 - ieeexplore.ieee.org
In this paper, breast cancer detection using convolutional neural network for mammogram
imaging system is proposed to classify mammogram image into normal, benign (non …

Should we ignore, follow, or biopsy? Impact of artificial intelligence decision support on breast ultrasound lesion assessment

VL Mango, M Sun, RT Wynn… - American Journal of …, 2020 - Am Roentgen Ray Soc
OBJECTIVE. The objective of this study was to assess the impact of artificial intelligence (AI)-
based decision support (DS) on breast ultrasound (US) lesion assessment. MATERIALS …

Artificial intelligence in healthcare in developing nations: The beginning of a transformative journey

A Mahajan, T Vaidya, A Gupta, S Rane… - Cancer Research …, 2019 - journals.lww.com
Introduction: Artificial intelligence (AI) is the fascinating result of the convergence of various
technologies, algorithms and approaches. Its role in early detection and diagnosis will be a …

Diagnosis of urinary tract infection based on artificial intelligence methods

IA Ozkan, M Koklu, IU Sert - Computer methods and programs in …, 2018 - Elsevier
Abstract Background and Objective Urinary tract infection (UTI) is a common disease
affecting the vast majority of people. UTI involves a simple infection caused by urinary tract …

Construction the model on the breast cancer survival analysis use support vector machine, logistic regression and decision tree

CM Chao, YW Yu, BW Cheng, YL Kuo - Journal of medical systems, 2014 - Springer
The aim of the paper is to use data mining technology to establish a classification of breast
cancer survival patterns, and offers a treatment decision-making reference for the survival …

Predicting breast cancer biopsy outcomes from BI-RADS findings using random forests with chi-square and MI features

S Williamson, K Vijayakumar, VJ Kadam - Multimedia Tools and …, 2022 - Springer
To look for early breast cancer signs and indications, mammography screening is one of the
best approaches available. Screening mammograms are the most commonly recognized …

Computer-assisted frameworks for classification of liver, breast and blood neoplasias via neural networks: A survey based on medical images

A Brunetti, L Carnimeo, GF Trotta, V Bevilacqua - Neurocomputing, 2019 - Elsevier
Abstract Computer Aided Diagnosis (CAD) systems can support physicians in classifying
different kinds of breast cancer, liver cancer and blood tumours also revealed by images …