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Connection

Frederick Howard to Humans

This is a "connection" page, showing publications Frederick Howard has written about Humans.
Connection Strength

0.567
  1. Generative adversarial networks accurately reconstruct pan-cancer histology from pathologic, genomic, and radiographic latent features. Sci Adv. 2024 Nov 15; 10(46):eadq0856.
    View in: PubMed
    Score: 0.032
  2. ASO Author Reflections: Breast-Conserving Surgery After Neoadjuvant Systemic Therapy for Early-Stage Breast Cancer: Quantitative Biomarkers and Disparities in the Precision-Medicine Era. Ann Surg Oncol. 2024 Dec; 31(13):8904-8905.
    View in: PubMed
    Score: 0.032
  3. Quantitative Biomarkers, Genomic Assays, and Demographics Associated with Breast-Conserving Surgery Following Neoadjuvant Therapy in Early-Stage, Hormone Receptor-Positive, HER-Negative Breast Cancer. Ann Surg Oncol. 2024 Dec; 31(13):8829-8842.
    View in: PubMed
    Score: 0.032
  4. Characterizing the Increase in Artificial Intelligence Content Detection in Oncology Scientific Abstracts From 2021 to 2023. JCO Clin Cancer Inform. 2024 May; 8:e2400077.
    View in: PubMed
    Score: 0.031
  5. Validation of the RSClin risk calculator in the National Cancer Data Base. Cancer. 2024 Apr 15; 130(8):1210-1220.
    View in: PubMed
    Score: 0.030
  6. Classification of Breast Cancer According to ERBB2 Immunohistochemistry Scores-Reply. JAMA Oncol. 2023 09 01; 9(9):1299-1300.
    View in: PubMed
    Score: 0.030
  7. Clinicopathologic Characteristics and Prognosis of ERBB2-Low Breast Cancer Among Patients in the National Cancer Database. JAMA Oncol. 2023 04 01; 9(4):500-510.
    View in: PubMed
    Score: 0.029
  8. The evolving therapeutic landscape of antibody-drug conjugates in breast cancer. Expert Rev Anticancer Ther. 2022 12; 22(12):1325-1331.
    View in: PubMed
    Score: 0.028
  9. Multimodal deep learning: An improvement in prognostication or a reflection of batch effect? Cancer Cell. 2023 01 09; 41(1):5-6.
    View in: PubMed
    Score: 0.028
  10. Highly accurate response prediction in high-risk early breast cancer patients using a biophysical simulation platform. Breast Cancer Res Treat. 2022 Nov; 196(1):57-66.
    View in: PubMed
    Score: 0.028
  11. Clinical trials of immunotherapy in triple-negative breast cancer. Breast Cancer Res Treat. 2022 Aug; 195(1):1-15.
    View in: PubMed
    Score: 0.027
  12. The emerging role of immune checkpoint inhibitors for the treatment of breast cancer. Expert Opin Investig Drugs. 2022 Jun; 31(6):531-548.
    View in: PubMed
    Score: 0.026
  13. The impact of site-specific digital histology signatures on deep learning model accuracy and bias. Nat Commun. 2021 07 20; 12(1):4423.
    View in: PubMed
    Score: 0.025
  14. Epidemiology of Triple-Negative Breast Cancer: A Review. Cancer J. 2021 Jan-Feb 01; 27(1):8-16.
    View in: PubMed
    Score: 0.025
  15. Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer. JAMA Netw Open. 2020 11 02; 3(11):e2025881.
    View in: PubMed
    Score: 0.024
  16. Implementation of an automated scheduling tool improves schedule quality and resident satisfaction. PLoS One. 2020; 15(8):e0236952.
    View in: PubMed
    Score: 0.024
  17. Prognosis and Treatment of Non-Small Cell Lung Cancer in the Age of Deep Learning. JAMA Netw Open. 2020 06 01; 3(6):e206368.
    View in: PubMed
    Score: 0.024
  18. Pneumococcal Bacteremia Complicated by Hemophagocytic Lymphohistiocytosis. J Gen Intern Med. 2019 08; 34(8):1653-1657.
    View in: PubMed
    Score: 0.022
  19. Predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer using a machine learning approach. Breast Cancer Res. 2024 Oct 29; 26(1):148.
    View in: PubMed
    Score: 0.008
  20. Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning. EBioMedicine. 2024 Sep; 107:105276.
    View in: PubMed
    Score: 0.008
  21. Bilateral asymmetry of quantitative parenchymal kinetics at ultrafast DCE-MRI predict response to neoadjuvant chemotherapy in patients with HER2+ breast cancer. Magn Reson Imaging. 2023 Dec; 104:9-15.
    View in: PubMed
    Score: 0.007
  22. Molecular profiling of a real-world breast cancer cohort with genetically inferred ancestries reveals actionable tumor biology differences between European ancestry and African ancestry patient populations. Breast Cancer Res. 2023 05 25; 25(1):58.
    View in: PubMed
    Score: 0.007
  23. The impact of race and age on response to neoadjuvant therapy and long-term outcomes in Black and White women with early-stage breast cancer. Breast Cancer Res Treat. 2023 Jul; 200(1):75-83.
    View in: PubMed
    Score: 0.007
  24. Response to Treatment, Racial and Ethnic Disparity, and Survival in Patients With Breast Cancer Undergoing Neoadjuvant Chemotherapy in the US. JAMA Netw Open. 2023 03 01; 6(3):e235834.
    View in: PubMed
    Score: 0.007
  25. Racial Disparities in Pathological Complete Response Among Patients Receiving Neoadjuvant Chemotherapy for Early-Stage Breast Cancer. JAMA Netw Open. 2023 03 01; 6(3):e233329.
    View in: PubMed
    Score: 0.007
  26. Towards Patient-Specific Optimization of Neoadjuvant Treatment Protocols for Breast Cancer Based on Image-Guided Fluid Dynamics. IEEE Trans Biomed Eng. 2022 11; 69(11):3334-3344.
    View in: PubMed
    Score: 0.007
  27. Development and Validation of a Decision Analytical Model for Posttreatment Surveillance for Patients With Oropharyngeal Carcinoma. JAMA Netw Open. 2022 04 01; 5(4):e227240.
    View in: PubMed
    Score: 0.007
  28. Differences Between Ipsilateral and Contralateral Early Parenchymal Enhancement Kinetics Predict Response of Breast Cancer to Neoadjuvant Therapy. Acad Radiol. 2022 10; 29(10):1469-1479.
    View in: PubMed
    Score: 0.007
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.