[HTML][HTML] Machine learning, IoT and 5G technologies for breast cancer studies: A review
Cancer is a life-threatening ailment characterized by the uncontrolled proliferation of cells.
Breast cancer (BC) represents the most highly infiltrative neoplasms and constitutes the …
Breast cancer (BC) represents the most highly infiltrative neoplasms and constitutes the …
[HTML][HTML] Computer-aided diagnosis for breast cancer classification using deep neural networks and transfer learning
Abstract Background and Objective: Many developed and non-developed countries
worldwide suffer from cancer-related fatal diseases. In particular, the rate of breast cancer in …
worldwide suffer from cancer-related fatal diseases. In particular, the rate of breast cancer in …
[PDF][PDF] Machine learning approach on healthcare big data: a review
In the past few years, big data has flattering more dominant in healthcare, due to three major
reasons, such as the huge amount of data available, expanding healthcare costs, and a …
reasons, such as the huge amount of data available, expanding healthcare costs, and a …
Classification of patients with breast cancer using neighbourhood component analysis and supervised machine learning techniques
S Laghmati, B Cherradi, A Tmiri… - 2020 3rd …, 2020 - ieeexplore.ieee.org
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 …
Breast cancer classification through meta-learning ensemble technique using convolution neural networks
This study aims to develop an efficient and accurate breast cancer classification model using
meta-learning approaches and multiple convolutional neural networks. This Breast …
meta-learning approaches and multiple convolutional neural networks. This Breast …
Machine learning based intelligent system for breast cancer prediction (MLISBCP)
Risks of death from Breast Cancer (BC) are drastically rising in recent years. The diagnosis
of breast cancer is time-consuming due to the limited availability of diagnostic systems such …
of breast cancer is time-consuming due to the limited availability of diagnostic systems such …
Deep hybrid architectures for diabetic retinopathy classification
Diabetic retinopathy (DR) is the most severe ocular complication of diabetes. It leads to
serious eye complications such as vision impairment and blindness. A computer-aided …
serious eye complications such as vision impairment and blindness. A computer-aided …
On the value of deep learning for diagnosing diabetic retinopathy
Diabetic retinopathy (DR) is one of the main causes of vision loss around the world. The
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …
early diagnosis of this disease can help in treating it efficiently. Deep learning (DL) is rapidly …
[HTML][HTML] Meta-Health Stack: A new approach for breast cancer prediction
Data analytics and machine learning have grown in importance to efficiently manage large
amounts of healthcare data. Recent statistics indicate that breast cancer is the most …
amounts of healthcare data. Recent statistics indicate that breast cancer is the most …
[HTML][HTML] A magnification-independent method for breast cancer classification using transfer learning
V Kumari, R Ghosh - Healthcare Analytics, 2023 - Elsevier
Breast cancer is the most common and diagnosed cancer among women worldwide.
Doctors use breast imaging reporting and data systems to classify breast density. This study …
Doctors use breast imaging reporting and data systems to classify breast density. This study …