[PDF][PDF] A systematic literature review of deep and machine learning algorithms in cardiovascular diseases diagnosis
During the whole cardiac cycle, heart sounds are created, and blood enters the heart
chambers as the cardiac regulators open and close. Blood flow produces aural noises; the …
chambers as the cardiac regulators open and close. Blood flow produces aural noises; the …
Literature review of breast cancer detection using machine learning algorithms
Cancer is the leading cause of non-accidental deaths worldwide. Specifically, nearly 10
million people died globally from cancer in the year 2020. Breast Cancer (BC) is a common …
million people died globally from cancer in the year 2020. Breast Cancer (BC) is a common …
[HTML][HTML] Convolution neural network for breast cancer detection and classification using deep learning
Objective: Early detection and precise diagnosis of breast cancer (BC) plays an essential
part in enhancing the diagnosis and improving the breast cancer survival rate of patients …
part in enhancing the diagnosis and improving the breast cancer survival rate of patients …
Breast cancer detection and classification using deep learning Xception algorithm
BS Abunasser, MRJ AL-Hiealy… - International …, 2022 - search.proquest.com
Breast Cancer (BC) is one of the leading cause of deaths worldwide. Approximately 10
million people pass away internationally from breast cancer in the year 2020. Breast Cancer …
million people pass away internationally from breast cancer in the year 2020. Breast Cancer …
Multiple brain tumor classification with dense CNN architecture using brain MRI images
Brain MR images are the most suitable method for detecting chronic nerve diseases such as
brain tumors, strokes, dementia, and multiple sclerosis. They are also used as the most …
brain tumors, strokes, dementia, and multiple sclerosis. They are also used as the most …
Classification of Alzheimer's disease using convolutional neural networks
Brain-related diseases are among the most difficult diseases due to their sensitivity, the
difficulty of performing operations, and their high costs. In contrast, the operation is not …
difficulty of performing operations, and their high costs. In contrast, the operation is not …
Detection of brain tumor using deep learning
HR Almadhoun, SS Abu-Naser - 2022 - philpapers.org
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of
intelligent machines or software that work and reacts like humans, some of the computer …
intelligent machines or software that work and reacts like humans, some of the computer …
Classification of anomalies in gastrointestinal tract using deep learning
IM Dheir, SS Abu-Naser - 2022 - philpapers.org
Automatic detection of diseases and anatomical landmarks in medical images by the use of
computers is important and considered a challenging process that could help medical …
computers is important and considered a challenging process that could help medical …
Fraudulent financial transactions detection using machine learning
MMM Megdad, SS Abu-Naser, BS Abu-Nasser - 2022 - philpapers.org
It is crucial to actively detect the risks of transactions in a financial company to improve
customer experience and minimize financial loss. In this study, we compare different …
customer experience and minimize financial loss. In this study, we compare different …
Feature-enhanced deep learning technique with soft attention for MRI-based brain tumor classification
BC Mohanty, PK Subudhi, R Dash… - International Journal of …, 2024 - Springer
Brain tumor classification using Magnetic Resonance Imaging (MRI) is a pivotal area in
medical diagnostics, with the potential to influence early detection and subsequent treatment …
medical diagnostics, with the potential to influence early detection and subsequent treatment …