2 citations · 2 across the 1 of their papers we have counts for
6 papers
Deep learning for detecting pulmonary tuberculosis via chest radiography: an international study across 10 countries
Sahar Kazemzadeh, Jin Yu, Shahar Jamshy +21
Tuberculosis (TB) is a top-10 cause of death worldwide. Though the WHO recommends chest radiographs (CXRs) for TB screening, the limited availability of CXR interpretation is a bar…
Deep learning-based survival prediction for multiple cancer types using histopathology images
Ellery Wulczyn, David F. Steiner, Zhaoyang Xu +7
Prognostic information at diagnosis has important implications for cancer treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and c…
Human-centric Metric for Accelerating Pathology Reports Annotation
Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li +4
Pathology reports contain useful information such as the main involved organ, diagnosis, etc. These information can be identified from the free text reports and used for large-scal…
Multimodal Multitask Representation Learning for Pathology Biobank Metadata Prediction
Wei-Hung Weng, Yuannan Cai, Angela Lin +2
Metadata are general characteristics of the data in a well-curated and condensed format, and have been proven to be useful for decision making, knowledge discovery, and also hetero…
Whole-Slide Image Focus Quality: Automatic Assessment and Impact on AI Cancer Detection
Timo Kohlberger, Yun Liu, Melissa Moran +6
Digital pathology enables remote access or consults and powerful image analysis algorithms. However, the slide digitization process can create artifacts such as out-of-focus (OOF).…
Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer
Kunal Nagpal, Davis Foote, Yun Liu +17
For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scorin…