Daniel Shao

ORCID: 0000-0001-5584-8277
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About
Contact & Profiles
Research Areas
  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Artificial Intelligence in Healthcare and Education
  • Colorectal Cancer Screening and Detection
  • Cell Image Analysis Techniques
  • Digital Imaging for Blood Diseases
  • Biomedical Text Mining and Ontologies

Brigham and Women's Hospital
2022-2024

Harvard University
2022-2024

Harvard–MIT Division of Health Sciences and Technology
2022

Massachusetts General Hospital
2022

Tissue phenotyping is a fundamental computational pathology (CPath) task in learning objective characterizations of histopathologic biomarkers anatomic pathology. However, whole-slide imaging (WSI) poses complex computer vision problem which the large-scale image resolutions WSIs and enormous diversity morphological phenotypes preclude data annotation. Current efforts have proposed using pretrained encoders with either transfer from natural datasets or self-supervised pretraining on...

10.48550/arxiv.2308.15474 preprint EN other-oa arXiv (Cornell University) 2023-01-01
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