From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
Structural crack detection using deep convolutional neural networks
Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …
range of computer vision problems. It has achieved encouraging results in numerous …
Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
Deep and machine learning techniques for medical imaging-based breast cancer: A comprehensive review
EH Houssein, MM Emam, AA Ali… - Expert Systems with …, 2021 - Elsevier
Breast cancer is the second leading cause of death for women, so accurate early detection
can help decrease breast cancer mortality rates. Computer-aided detection allows …
can help decrease breast cancer mortality rates. Computer-aided detection allows …
Computational technique based on machine learning and image processing for medical image analysis of breast cancer diagnosis
VDP Jasti, AS Zamani, K Arumugam… - Security and …, 2022 - Wiley Online Library
Breast cancer is the most lethal type of cancer for all women worldwide. At the moment,
there are no effective techniques for preventing or curing breast cancer, as the source of the …
there are no effective techniques for preventing or curing breast cancer, as the source of the …
[HTML][HTML] Deep learning approaches to biomedical image segmentation
IRI Haque, J Neubert - Informatics in Medicine Unlocked, 2020 - Elsevier
The review covers automatic segmentation of images by means of deep learning
approaches in the area of medical imaging. Current developments in machine learning …
approaches in the area of medical imaging. Current developments in machine learning …
COVID-19 prediction and detection using deep learning
Currently, the detection of coronavirus disease 2019 (COVID-19) is one of the main
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
Global guidance network for breast lesion segmentation in ultrasound images
Automatic breast lesion segmentation in ultrasound helps to diagnose breast cancer, which
is one of the dreadful diseases that affect women globally. Segmenting breast regions …
is one of the dreadful diseases that affect women globally. Segmenting breast regions …
Machine learning techniques for biomedical image segmentation: an overview of technical aspects and introduction to state‐of‐art applications
H Seo, M Badiei Khuzani, V Vasudevan… - Medical …, 2020 - Wiley Online Library
In recent years, significant progress has been made in developing more accurate and
efficient machine learning algorithms for segmentation of medical and natural images. In this …
efficient machine learning algorithms for segmentation of medical and natural images. In this …
Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods
Abstract The Global Cancer Statistics 2020 reported breast cancer (BC) as the most
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …
common diagnosis of cancer type. Therefore, early detection of such type of cancer would …