Matthew H. Bailey

Brigham Young University

Full Professor(heuristic)

Radiomics and Machine Learning in Medical Imaging · Radiology, Nuclear Medicine and Imaging

h-index60

i10-index83

Publications260

Citations54,854

Grants

No NSF/NIH grants on record.

Career Trajectory

Research Cluster Map

Direct collaborators. Node size = influence, colour = community, dashed = past collaboration.

Potential Collaborators

Recent Publications

Last 2 years · showing 20 of 68

Figure S11 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S2 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S6 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S1 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
PDXNet consortium members from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Supplementary Data from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S3 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S5 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S8 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S4 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S10 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S15 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S12 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Supplementary Data from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S14 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S9 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S7 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Figure S13 from A Pan-Cancer Patient-Derived Xenograft Histology Image Repository with Genomic and Pathologic Annotations Enables Deep Learning Analysis
2026-06-17
Phenome-Wide Association Study of Pre-Cancer Diagnosis Electronic Health Records Identifies Risk and Inverse Associations in the All of Us Research Program
medRxiv · 2026-05-28
Abstract 2721: Phenome-wide association study of pre-cancer diagnosis electronic health records identifies risk and protective factors in the All of Us Research Program.
Cancer Research · 2026-04-03

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