Recent advancements in artificial intelligence for breast cancer: Image augmentation, segmentation, diagnosis, and prognosis approaches
Breast cancer is a significant global health burden, with increasing morbidity and mortality
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
worldwide. Early screening and accurate diagnosis are crucial for improving prognosis …
Pre-training in medical data: A survey
Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …
part of a clinical trial program. There are many categories of such data, such as clinical …
Vision-transformer-based transfer learning for mammogram classification
Breast mass identification is a crucial procedure during mammogram-based early breast
cancer diagnosis. However, it is difficult to determine whether a breast lump is benign or …
cancer diagnosis. However, it is difficult to determine whether a breast lump is benign or …
Mammography and ultrasound based dual modality classification of breast cancer using a hybrid deep learning approach
Traditional methods of diagnosing breast cancer (BC) suffer from human errors, are less
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
accurate, and consume time. A computer-aided detection (CAD) system can overcome the …
A novel transfer learning-based model for ultrasound breast cancer image classification
Breast cancer is the second most dangerous disease for women after lung cancer. As in
most diseases, an early detection and the corresponding treatment of breast cancer …
most diseases, an early detection and the corresponding treatment of breast cancer …
BUVITNET: Breast ultrasound detection via vision transformers
Convolutional neural networks (CNNs) have enhanced ultrasound image-based early
breast cancer detection. Vision transformers (ViTs) have recently surpassed CNNs as the …
breast cancer detection. Vision transformers (ViTs) have recently surpassed CNNs as the …
[HTML][HTML] A novel fusion framework of deep bottleneck residual convolutional neural network for breast cancer classification from mammogram images
With over 2.1 million new cases of breast cancer diagnosed annually, the incidence and
mortality rate of this disease pose severe global health issues for women. Identifying the …
mortality rate of this disease pose severe global health issues for women. Identifying the …
Ultrasound-responsive nanocarriers for breast cancer chemotherapy
Breast cancer is the most common type of cancer and it is treated with surgical intervention,
radiotherapy, chemotherapy, or a combination of these regimens. Despite chemotherapy's …
radiotherapy, chemotherapy, or a combination of these regimens. Despite chemotherapy's …
Diagnostic strategies for breast cancer detection: from image generation to classification strategies using artificial intelligence algorithms
JA Basurto-Hurtado, IA Cruz-Albarran… - Cancers, 2022 - mdpi.com
Simple Summary With the recent advances in the field of artificial intelligence, it has been
possible to develop robust and accurate methodologies that can deliver noticeable results in …
possible to develop robust and accurate methodologies that can deliver noticeable results in …
Automated breast tumor ultrasound image segmentation with hybrid UNet and classification using fine-tuned CNN model
Introduction Breast cancer stands as the second most deadly form of cancer among women
worldwide. Early diagnosis and treatment can significantly mitigate mortality rates. Purpose …
worldwide. Early diagnosis and treatment can significantly mitigate mortality rates. Purpose …