Explainable, domain-adaptive, and federated artificial intelligence in medicine
Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in
each domain is driven by a growing body of annotated data, increased computational …
each domain is driven by a growing body of annotated data, increased computational …
Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Deep learning has demonstrated remarkable performance across various tasks in medical
imaging. However, these approaches primarily focus on supervised learning, assuming that …
imaging. However, these approaches primarily focus on supervised learning, assuming that …
An optimized deep learning architecture for breast cancer diagnosis based on improved marine predators algorithm
EH Houssein, MM Emam, AA Ali - Neural computing and applications, 2022 - Springer
Breast cancer is the second leading cause of death in women; therefore, effective early
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
detection of this cancer can reduce its mortality rate. Breast cancer detection and …
Deep learning-enabled fully automated pipeline system for segmentation and classification of single-mass breast lesions using contrast-enhanced mammography: a …
T Zheng, F Lin, X Li, T Chu, J Gao, S Zhang, Z Li… - …, 2023 - thelancet.com
Background Breast cancer is the leading cause of cancer-related deaths in women.
However, accurate diagnosis of breast cancer using medical images heavily relies on the …
However, accurate diagnosis of breast cancer using medical images heavily relies on the …
[HTML][HTML] Artificial intelligence breakthroughs in pioneering early diagnosis and precision treatment of breast cancer: A multimethod study
This article delves into the potential of artificial intelligence (AI) to enhance early breast
cancer (BC) detection for improved treatment outcomes and patient care. Utilizing a …
cancer (BC) detection for improved treatment outcomes and patient care. Utilizing a …
A review on computational methods for breast cancer detection in ultrasound images using multi-image modalities
Breast cancer is a kind of cancer that develops and propagates from tissues of the breast
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …
and slowly transcends the whole body, this type of tumor is found in both sexes. Early …
Deep ensemble transfer learning-based framework for mammographic image classification
This research intends to provide a method for clinical decision support systems that can
accurately classify benign and malignant mass from breast X-ray images. The model was …
accurately classify benign and malignant mass from breast X-ray images. The model was …
[HTML][HTML] Performance evaluation of deep learning models on mammogram classification using small dataset
Cancer is the second leading cause of death globally, and breast cancer (BC) is the second
most reported cancer. Although the incidence rate is reducing in developed countries, the …
most reported cancer. Although the incidence rate is reducing in developed countries, the …
Towards robust natural-looking mammography lesion synthesis on ipsilateral dual-views breast cancer analysis
In recent years, many mammographic image analysis methods have been introduced for
improving cancer classification tasks. Two major issues of mammogram classification tasks …
improving cancer classification tasks. Two major issues of mammogram classification tasks …
A dual meta-learning framework based on idle data for enhancing segmentation of pancreatic cancer
Automated segmentation of pancreatic cancer is vital for clinical diagnosis and treatment.
However, the small size and inconspicuous boundaries limit the segmentation performance …
However, the small size and inconspicuous boundaries limit the segmentation performance …