Matthew H. Bailey
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Recognitions
Matthew H. Bailey has a total of 1000 co-authors. Here are the top co-authors by number of shared publications:
- Li Ding
Washington University in St. Louis
105 shared publications - Alana L. Welm
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA
92 shared publications - R. Jay Mashl
Department of Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri
92 shared publications - Ali Foroughi pour
The Jackson Laboratory for Genomic Medicine, Farmington, CT
91 shared publications - Bingliang Fang
Department of Thoracic and Cardiovascular Surgery, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
91 shared publications - Brandi N. Davis-Dusenbery
Seven Bridges Genomics
91 shared publications
Latest Publications
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S11 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S11 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S11 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S11 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S2 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S2 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S2 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S2 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S8 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S8 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S8 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
Figure S8 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis