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Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review
NIR Yassin, S Omran, EMF El Houby… - Computer methods and …, 2018 - Elsevier
Background and objective The high incidence of breast cancer in women has increased
significantly in the recent years. Physician experience of diagnosing and detecting breast …
significantly in the recent years. Physician experience of diagnosing and detecting breast …
[HTML][HTML] Early detection of the breast cancer using infrared technology–A comprehensive review
Breast cancer is one of the most common and deadly diseases in women, which can also
affect men. Early detection and treatment of this disease can increase the chances of cure …
affect men. Early detection and treatment of this disease can increase the chances of cure …
CAD and AI for breast cancer—recent development and challenges
Computer-aided diagnosis (CAD) has been a popular area of research and development in
the past few decades. In CAD, machine learning methods and multidisciplinary knowledge …
the past few decades. In CAD, machine learning methods and multidisciplinary knowledge …
Radiomics and machine learning analysis based on magnetic resonance imaging in the assessment of liver mucinous colorectal metastases
Purpose The purpose of this study is to evaluate the Radiomics and Machine Learning
Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases. Query …
Analysis based on MRI in the assessment of Liver Mucinous Colorectal Metastases. Query …
Radiomics in medical imaging: pitfalls and challenges in clinical management
Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …
An introduction and overview of machine learning in neurosurgical care
Background Machine learning (ML) is a branch of artificial intelligence that allows computers
to learn from large complex datasets without being explicitly programmed. Although ML is …
to learn from large complex datasets without being explicitly programmed. Although ML is …
Radiomic analysis reveals DCE-MRI features for prediction of molecular subtypes of breast cancer
The purpose of this study was to investigate the role of features derived from breast dynamic
contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical …
contrast-enhanced magnetic resonance imaging (DCE-MRI) and to incorporated clinical …
[HTML][HTML] Prediction of breast cancer histological outcome by radiomics and artificial intelligence analysis in contrast-enhanced mammography
A Petrillo, R Fusco, E Di Bernardo, T Petrosino… - Cancers, 2022 - mdpi.com
Simple Summary The assessment of breast lesions through mammographic images is
currently challenging, especially in dense breasts. Contrast-enhanced mammography has …
currently challenging, especially in dense breasts. Contrast-enhanced mammography has …
[HTML][HTML] Preliminary report on computed tomography radiomics features as biomarkers to immunotherapy selection in lung adenocarcinoma patients
Simple Summary The objective of the study was to assess the radiomics features obtained
by computed tomography (CT) examination as biomarkers in order to select patients with …
by computed tomography (CT) examination as biomarkers in order to select patients with …
Classification of patients with breast cancer using neighbourhood component analysis and supervised machine learning techniques
Breast cancer is considered one of the leading causes of death among women. In morocco,
the ministry of health reports over 40.000 new cases each year. When lifestyle can be a …
the ministry of health reports over 40.000 new cases each year. When lifestyle can be a …