Daniel Marcus, PhD

Medical School Department Radiology
Research Program Oncologic Imaging
Daniel Marcus

Researcher Background

Primary Academic Title

Professor of Radiology, WashU Medicine

Education

  • 2001: PhD, Washington University, St. Louis, MO

Research & Selected Publications

Research Interest

Medical imaging informatics and analysis. Developing the Comprehensive Neuro-oncology Data Repository (CONDR), an integrated database of MRI, PET, clinical, pathology and genetic data. The long-term goal is to develop a resource for exploring advanced imaging and the genetics of brain cancers.

Research Publications

The ADAPT learning cancer treatment system: ARPA-H's initiative to revolutionize cancer therapy.
Authors:

Bild AH, Sangar MC, McQuerry JA, one or more additional authors omitted Marcus D, one or more additional authors omitted Eddy JA

Journal & Year:

Cancer Cell • 2026

The ADAPT learning cancer treatment system: ARPA-H's initiative to revolutionize cancer therapy.
Authors:

Bild AH, Sangar MC, McQuerry JA, one or more additional authors omitted Marcus D, one or more additional authors omitted Eddy JA

Journal & Year:

Cancer Cell • 2026

Large-Scale Evaluation of Machine Learning Models in Identifying Follow-Up Recommendations in Radiology Reports.
Authors:

Xiao P, Yu X, Ha SM, one or more additional authors omitted Marcus DS, one or more additional authors omitted Sotiras A

Journal & Year:

Radiology • 2025

Large-Scale Evaluation of Machine Learning Models in Identifying Follow-Up Recommendations in Radiology Reports.
Authors:

Xiao P, Yu X, Ha SM, one or more additional authors omitted Marcus DS, one or more additional authors omitted Sotiras A

Journal & Year:

Radiology • 2025

Informatics at the Frontier of Cancer Research.
Authors:

Noller K, Botsis T, Camara PG, one or more additional authors omitted Marcus D, one or more additional authors omitted Bakas S

Journal & Year:

Cancer Res • 2025

Informatics at the Frontier of Cancer Research.
Authors:

Noller K, Botsis T, Camara PG, one or more additional authors omitted Marcus D, one or more additional authors omitted Bakas S

Journal & Year:

Cancer Res • 2025

Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge.
Authors:

Zenk M, Baid U, Pati S, one or more additional authors omitted Marcus DS, one or more additional authors omitted Bakas S

Journal & Year:

Nat Commun • 2025

Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge.
Authors:

Zenk M, Baid U, Pati S, one or more additional authors omitted Marcus DS, one or more additional authors omitted Bakas S

Journal & Year:

Nat Commun • 2025