The state of the art for artificial intelligence in lung digital pathology

VS Viswanathan, P Toro, G Corredor… - The Journal of …, 2022 - Wiley Online Library
Lung diseases carry a significant burden of morbidity and mortality worldwide. The advent of
digital pathology (DP) and an increase in computational power have led to the development …

[HTML][HTML] Emerging Technologies in Medicine: Artificial Intelligence, Robotics, and Medical Automation

M Rezaei, S Saei, SJ Khouzani, ME Rostami… - Kindle, 2023 - preferpub.org
The healthcare industry is undergoing a profound transformation with the emergence of
revolutionary technologies like artificial intelligence (AI), robotics, and medical automation …

A population-level digital histologic biomarker for enhanced prognosis of invasive breast cancer

M Amgad, JM Hodge, MAT Elsebaie, C Bodelon… - Nature Medicine, 2024 - nature.com
Breast cancer is a heterogeneous disease with variable survival outcomes. Pathologists
grade the microscopic appearance of breast tissue using the Nottingham criteria, which are …

Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade

MA Berbís, DS McClintock, A Bychkov… - …, 2023 - thelancet.com
Background Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the
practice of pathology. However, clinical integration remains challenging, with no AI …

[HTML][HTML] Artificial intelligence in cancer care: From diagnosis to prevention and beyond

M Farrokhi, A Moeini, F Taheri, M Farrokhi, M Mostafavi… - Kindle, 2023 - preferpub.org
Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care,
encompassing various aspects from diagnosis to prevention and beyond. With its ability to …

A generalizable and robust deep learning algorithm for mitosis detection in multicenter breast histopathological images

X Wang, J Zhang, S Yang, J Xiang, F Luo, M Wang… - Medical image …, 2023 - Elsevier
Mitosis counting of biopsies is an important biomarker for breast cancer patients, which
supports disease prognostication and treatment planning. Developing a robust mitotic cell …

Artificial intelligence in endodontic education

A Aminoshariae, A Nosrat, V Nagendrababu… - Journal of …, 2024 - Elsevier
Aims The future dental and endodontic education must adapt to the current digitalized
healthcare system in a hyper-connected world. The purpose of this scoping review was to …

Deep learning model improves tumor-infiltrating lymphocyte evaluation and therapeutic response prediction in breast cancer

S Choi, SI Cho, W Jung, T Lee, SJ Choi, S Song… - NPJ Breast …, 2023 - nature.com
Tumor-infiltrating lymphocytes (TILs) have been recognized as key players in the tumor
microenvironment of breast cancer, but substantial interobserver variability among …

Clinical implication of low estrogen receptor (ER-low) expression in breast cancer

T Reinert, F Cascelli, CAA Resende… - Frontiers in …, 2022 - frontiersin.org
Breast cancer is a heterogeneous disease, and the estrogen receptor (ER) remains the most
important biomarker in breast oncology. Most guidelines set a positive expression threshold …

[HTML][HTML] Unusual patterns of HER2 expression in breast cancer: Insights and perspectives

D Grassini, E Cascardi, I Sarotto, L Annaratone… - Pathobiology, 2022 - karger.com
The biomarker human epidermal growth factor receptor-2 (HER2) has represented the best
example of successful targeted therapy in breast cancer patients. Based on the concept of …