Deep learning in breast cancer imaging: A decade of progress and future directions

L Luo, X Wang, Y Lin, X Ma, A Tan… - IEEE Reviews in …, 2024 - ieeexplore.ieee.org
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Applications of artificial intelligence in breast pathology

Y Liu, D Han, AV Parwani, Z Li - Archives of pathology & …, 2023 - meridian.allenpress.com
Context.—Increasing implementation of whole slide imaging together with digital workflow
and advances in computing capacity enable the use of artificial intelligence (AI) in …

Artificial intelligence's impact on breast cancer pathology: a literature review

A Soliman, Z Li, AV Parwani - Diagnostic pathology, 2024 - Springer
This review discusses the profound impact of artificial intelligence (AI) on breast cancer (BC)
diagnosis and management within the field of pathology. It examines the various …

IVNet: Transfer learning based diagnosis of breast cancer grading using histopathological images of infected cells

S Aziz, K Munir, A Raza, MS Almutairi, S Nawaz - IEEE Access, 2023 - ieeexplore.ieee.org
Breast cancer constitutes a significant global health concern that impacts millions of women
across the world. The diagnosis of breast cancer involves categorizing grades based on the …

Comparative evaluation of breast ductal carcinoma grading: A deep-learning model and general Pathologists' assessment approach

MM Köteles, A Vigdorovits, D Kumar, IM Mihai… - Diagnostics, 2023 - mdpi.com
Breast cancer is the most prevalent neoplasia among women, with early and accurate
diagnosis critical for effective treatment. In clinical practice, however, the subjective nature of …

From Reductionistic Approach to Systems Immunology Approach for the Understanding of Tumor Microenvironment

N Koelsch, MH Manjili - International Journal of Molecular Sciences, 2023 - mdpi.com
The tumor microenvironment (TME) is a complex and dynamic ecosystem that includes a
variety of immune cells mutually interacting with tumor cells, structural/stromal cells, and …

Accuracy and Utility of Preoperative Ultrasound‐Guided Axillary Lymph Node Biopsy for Invasive Breast Cancer: A Systematic Review and Meta‐Analysis

Y Huang, S Zheng, Y Lin - Computational Intelligence and …, 2022 - Wiley Online Library
Background. With the acceleration of the pace of life and work, the incidence rate of invasive
breast cancer is getting higher and higher, and early diagnosis is very important. This study …

Current status and prospects of artificial intelligence in breast cancer pathology: convolutional neural networks to prospective Vision Transformers

A Katayama, Y Aoki, Y Watanabe, J Horiguchi… - International Journal of …, 2024 - Springer
Breast cancer is the most prevalent cancer among women, and its diagnosis requires the
accurate identification and classification of histological features for effective patient …

Impact of Tumor‐Infiltrating Lymphocytes on Disease Progression in Human Papillomavirus‐Related Oropharyngeal Carcinoma

LX Yin, M Rivera, JJ Garcia… - … –Head and Neck …, 2023 - Wiley Online Library
Objective We aim to explore the prognostic value of tumor‐infiltrating lymphocytes (TILs) in
the primary tumor and metastatic lymph nodes of patients with HPV (+) OPSCC. We …

Deep learning-based risk stratification of preoperative breast biopsies using digital whole slide images

C Boissin, Y Wang, A Sharma, P Weitz… - Breast Cancer …, 2024 - Springer
Background Nottingham histological grade (NHG) is a well established prognostic factor in
breast cancer histopathology but has a high inter-assessor variability with many tumours …