JS
Joseph Sparano
Icahn School of Medicine at Mount Sinai
Research areas: Biochemistry, Genetics and Molecular Biology · Cancer Research · Breast Cancer Treatment Studies · Cancer Treatment and Pharmacology · Advanced Breast Cancer Therapies
0000-0002-9031-2010
Employment
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Icahn School of Medicine at Mount Sinai Chief, Division of Hematology/Oncology; Deputy Director, Tisch Cancer Institute2021 - Present
Education
Education history is unavailable.
Projects & Funding
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Collection and Storage of Biospecimens in ECOG-ACRIN Adjuvant Trials The Breast Cancer Research Foundation Inc.2023 - 2024
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The ECOG-ACRIN Lobular Breast Cancer Initiative The Breast Cancer Research Foundation Inc.2023 - 2024
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The characterization and evaluation of lobular cancer in ECOG-ACRIN phase III trials and Biospecimen and Imaging Bank for Determinants of Late Relapse in Operable Breast Cancer The Breast Cancer Research Foundation Inc.2022 - 2023
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Support for ECOG-ACRIN Sponsored Clinical Trials by The Breast Cancer Research Foundation The Breast Cancer Research Foundation Inc.2022 - 2023
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The characterization and evaluation of lobular cancer in ECOG-ACRIN phase III trials and Biospecimen Bank for Determinants of Late Relapse in Operable Breast Cancer The Breast Cancer Research Foundation Inc.2021 - 2022
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Support for ECOG-ACRIN Sponsored Clinical Trials by The Breast Cancer Research Foundation The Breast Cancer Research Foundation Inc.2021 - 2022
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North American Breast Cancer Groups Biospecimen Bank for Determinants of Late Relapse in Operable Breast Cancer The Breast Cancer Research Foundation Inc.2018 - 2019
Publications (311)
- Nivolumab and cabozantinib in people with HIV and advanced solid tumors: a pilot trial and systematic review Save
- Racial disparities in breast cancer: looking beyond the recurrence score Save
- Data from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 1 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 2 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 3 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 4 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 5 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Figure 6 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Code from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Figure 1 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Figure 2 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Figure 3 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Figure 4 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Methods from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Table 1 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Table 10 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Table 11 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Table 12 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save
- Supplementary Table 13 from Development and Validation of a Multimodal–Multitask Deep Learning Approach for Estimating Late Distant Recurrence Risk in HR-Positive Early Breast Cancer Save