Deep machine learning for medical diagnosis, application to lung cancer detection: a review
Deep learning has emerged as a powerful tool for medical image analysis and diagnosis,
demonstrating high performance on tasks such as cancer detection. This literature review …
demonstrating high performance on tasks such as cancer detection. This literature review …
Medical images segmentation for lung cancer diagnosis based on deep learning architectures
Lung cancer presents one of the leading causes of mortalities for people around the world.
Lung image analysis and segmentation are one of the primary steps used for early …
Lung image analysis and segmentation are one of the primary steps used for early …
Clinical decision support framework for segmentation and classification of brain tumor MRIs using a U-Net and DCNN cascaded learning algorithm
Brain tumors (BTs) are an uncommon but fatal kind of cancer. Therefore, the development of
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
computer-aided diagnosis (CAD) systems for classifying brain tumors in magnetic …
[HTML][HTML] Hydrogels with Essential Oils: Recent Advances in Designs and Applications
M Chelu - Gels, 2024 - pmc.ncbi.nlm.nih.gov
The innovative fusion of essential oils with hydrogel engineering offers an optimistic
perspective for the design and development of next-generation materials incorporating …
perspective for the design and development of next-generation materials incorporating …
Region‐Based Segmentation and Classification for Ovarian Cancer Detection Using Convolution Neural Network
Ovarian cancer is a serious sickness for elderly women. According to data, it is the seventh
leading cause of death in women as well as the fifth most frequent disease worldwide. Many …
leading cause of death in women as well as the fifth most frequent disease worldwide. Many …
A survey and taxonomy of 2.5 D approaches for lung segmentation and nodule detection in CT images
CAD systems for lung cancer diagnosis and detection can significantly offer unbiased,
infatiguable diagnostics with minimal variance, decreasing the mortality rate and the five …
infatiguable diagnostics with minimal variance, decreasing the mortality rate and the five …
[HTML][HTML] The Rise of Hypothesis-Driven Artificial Intelligence in Oncology
Cancer is a complex disease involving the deregulation of intricate cellular systems beyond
genetic aberrations and, as such, requires sophisticated computational approaches and …
genetic aberrations and, as such, requires sophisticated computational approaches and …
Comparative Study on Architecture of Deep Neural Networks for Segmentation of Brain Tumor using Magnetic Resonance Images
The state-of-the-art works for the segmentation of brain tumor using the images acquired by
Magnetic Resonance Imaging (MRI) with their performances are analyzed in this …
Magnetic Resonance Imaging (MRI) with their performances are analyzed in this …
A user-friendly deep learning application for accurate lung cancer diagnosis
BACKGROUND: Accurate diagnosis and subsequent delineated treatment planning require
the experience of clinicians in the handling of their case numbers. However, applying deep …
the experience of clinicians in the handling of their case numbers. However, applying deep …