[HTML][HTML] Artificial intelligence in breast cancer diagnosis and personalized medicine
Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …
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 …
and advances in computing capacity enable the use of artificial intelligence (AI) in …
Wsi-vqa: Interpreting whole slide images by generative visual question answering
Whole slide imaging is routinely adopted for carcinoma diagnosis and prognosis. Abundant
experience is required for pathologists to achieve accurate and reliable diagnostic results of …
experience is required for pathologists to achieve accurate and reliable diagnostic results of …
Deep learning-based prediction of molecular tumor biomarkers from H&E: a practical review
HD Couture - Journal of Personalized Medicine, 2022 - mdpi.com
Molecular and genomic properties are critical in selecting cancer treatments to target
individual tumors, particularly for immunotherapy. However, the methods to assess such …
individual tumors, particularly for immunotherapy. However, the methods to assess such …
Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence
Simple Summary Risk assessment in early breast cancer is critical for clinical decisions, but
defining risk categories poses a significant challenge. The integration of conventional …
defining risk categories poses a significant challenge. The integration of conventional …
Phikon-v2, a large and public feature extractor for biomarker prediction
Gathering histopathology slides from over 100 publicly available cohorts, we compile a
diverse dataset of 460 million pathology tiles covering more than 30 cancer sites. Using this …
diverse dataset of 460 million pathology tiles covering more than 30 cancer sites. Using this …
PhiHER2: phenotype-informed weakly supervised model for HER2 status prediction from pathological images
C Yan, J Sun, Y Guan, J Feng, H Liu, J Liu - Bioinformatics, 2024 - academic.oup.com
Motivation Human epidermal growth factor receptor 2 (HER2) status identification enables
physicians to assess the prognosis risk and determine the treatment schedule for patients. In …
physicians to assess the prognosis risk and determine the treatment schedule for patients. In …
Point Transformer with Federated Learning for Predicting Breast Cancer HER2 Status from Hematoxylin and Eosin-Stained Whole Slide Images
Directly predicting human epidermal growth factor receptor 2 (HER2) status from widely
available hematoxylin and eosin (HE)-stained whole slide images (WSIs) can reduce …
available hematoxylin and eosin (HE)-stained whole slide images (WSIs) can reduce …
Weakly-supervised deep learning models enable HER2-low prediction from H &E stained slides
Background Human epidermal growth factor receptor 2 (HER2)-low breast cancer has
emerged as a new subtype of tumor, for which novel antibody–drug conjugates have shown …
emerged as a new subtype of tumor, for which novel antibody–drug conjugates have shown …
Vision Transformers for Breast Cancer Human Epidermal Growth Factor Receptor 2 Expression Staging without Immunohistochemical Staining
Accurate staging of human epidermal growth factor receptor 2 (HER2) expression is vital for
evaluating breast cancer treatment efficacy. However, it typically involves costly and …
evaluating breast cancer treatment efficacy. However, it typically involves costly and …