Deep learning based methods for breast cancer diagnosis: a systematic review and future direction
Breast cancer is one of the precarious conditions that affect women, and a substantive cure
has not yet been discovered for it. With the advent of Artificial intelligence (AI), recently, deep …
has not yet been discovered for it. With the advent of Artificial intelligence (AI), recently, deep …
A comprehensive review for breast histopathology image analysis using classical and deep neural networks
Breast cancer is one of the most common and deadliest cancers among women. Since
histopathological images contain sufficient phenotypic information, they play an …
histopathological images contain sufficient phenotypic information, they play an …
Breast cancer detection in mammography images using deep convolutional neural networks and fuzzy ensemble modeling techniques
Breast cancer has evolved as the most lethal illness impacting women all over the globe.
Breast cancer may be detected early, which reduces mortality and increases the chances of …
Breast cancer may be detected early, which reduces mortality and increases the chances of …
Hyperparameter optimizer with deep learning-based decision-support systems for histopathological breast cancer diagnosis
Simple Summary This study develops an arithmetic optimization algorithm with deep-
learning-based histopathological breast cancer classification (AOADL-HBCC) technique for …
learning-based histopathological breast cancer classification (AOADL-HBCC) technique for …
Application of transfer learning and ensemble learning in image-level classification for breast histopathology
Background Breast cancer has the highest prevalence among all cancers in women
globally. The classification of histopathological images in the diagnosis of breast cancers is …
globally. The classification of histopathological images in the diagnosis of breast cancers is …
A comprehensive survey on deep-learning-based breast cancer diagnosis
Simple Summary Breast cancer was diagnosed in 2.3 million women, and around 685,000
deaths from breast cancer were recorded globally in 2020, making it the most common …
deaths from breast cancer were recorded globally in 2020, making it the most common …
Conventional machine learning versus deep learning for magnification dependent histopathological breast cancer image classification: A comparative study with …
Breast cancer is a serious threat to women. Many machine learning-based computer-aided
diagnosis (CAD) methods have been proposed for the early diagnosis of breast cancer …
diagnosis (CAD) methods have been proposed for the early diagnosis of breast cancer …
Multi-classification of breast cancer lesions in histopathological images using DEEP_Pachi: Multiple self-attention head
Introduction and Background: Despite fast developments in the medical field, histological
diagnosis is still regarded as the benchmark in cancer diagnosis. However, the input image …
diagnosis is still regarded as the benchmark in cancer diagnosis. However, the input image …
Improving cervical cancer classification with imbalanced datasets combining taming transformers with T2T-ViT
C Zhao, R Shuai, L Ma, W Liu, M Wu - Multimedia tools and applications, 2022 - Springer
Cervical cell classification has important clinical significance in cervical cancer screening at
early stages. However, there are fewer public cervical cancer smear cell datasets, the …
early stages. However, there are fewer public cervical cancer smear cell datasets, the …
[HTML][HTML] Computational pathology: a survey review and the way forward
Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …
developments of computational approaches to analyze and model medical histopathology …