The analysis of histopathology images with artificial intelligence aims to enable clinical decision support systems and precision medicine. The success of such applications depends …
Lymph node evaluation for the presence of breast cancer metastases is a critical component of breast cancer staging and treatment planning. Artificial intelligence tools for …
We present a deep learning AI algorithm designed to assist pathologists in detecting breast cancer lymph node metastases. In a reader study, pathologists using the AI system …
We present a machine learning approach for subtyping invasive carcinomas and high-risk lesions in breast pathology whole slide images. Our system leverages deep learning to …
We present a weakly supervised machine learning approach for morphological subtyping of breast cancer in whole slide images. Our system classifies invasive breast carcinomas into …
Reflectance confocal microscopy (RCM) is an effective, non-invasive pre-screening tool for cancer diagnosis. However, acquiring and reading RCM images requires extensive training …
We present a weakly supervised deep learning approach for morphological subtyping of breast cancer in whole slide images. Using image-level labels, our neural network system …
Reflectance confocal microscopy (RCM) is a non-invasive imaging tool widely used for skin cancer screening. Automated analysis of RCM images requires pixel-level annotations, which …
We present a clinical-grade machine learning system for detecting breast cancer in biopsies and excisions. The system was developed and validated on a large dataset of whole slide …
In-vivo optical microscopy is advancing into routine clinical practice for non-invasively guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce …