Hemant Ishwaran

Active 1996–2026

86
Papers
22,422
Citations
54
h-index
75
i10-index

Citations

Citations per year for Hemant Ishwaran1979: 1 citations1983: 1 citations1988: 1 citations1991: 1 citations1999: 3 citations2000: 9 citations2001: 13 citations2002: 22 citations2003: 30 citations2004: 37 citations2005: 49 citations2006: 83 citations2007: 95 citations2008: 116 citations2009: 111 citations2010: 165 citations2011: 168 citations2012: 170 citations2013: 171 citations2014: 250 citations2015: 252 citations2016: 408 citations2017: 402 citations2018: 422 citations2019: 890 citations2020: 1,056 citations2021: 1,091 citations2022: 858 citations2023: 675 citations2024: 924 citations2025: 469 citations2026: 66 citations1980–1982: no citations, so these years are not shown1984–1987: no citations, so these years are not shown1989–1990: no citations, so these years are not shown1992–1998: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 3,220 citing papers, 28.8% of this breakdownChina: 1,766 citing papers, 15.8% of this breakdownUnited Kingdom: 656 citing papers, 5.9% of this breakdownGermany: 503 citing papers, 4.5% of this breakdownItaly: 439 citing papers, 3.9% of this breakdownCanada: 406 citing papers, 3.6% of this breakdownFrance: 358 citing papers, 3.2% of this breakdownAustralia: 286 citing papers, 2.5% of this breakdownJapan: 285 citing papers, 2.5% of this breakdownNetherlands: 284 citing papers, 2.5% of this breakdownSpain: 243 citing papers, 2.2% of this breakdownSouth Korea: 210 citing papers, 1.9% of this breakdown
0%28.8%Other 22.7%

Fields

  • Medicine39.9%
  • Computer Science19.8%
  • Biochemistry, Genetics and Molecular Biology17.6%
  • Immunology and Microbiology6.5%
  • Mathematics5%
  • Engineering3.6%
  • Other7.6%

Topics

  • Cancer Immunotherapy and Biomarkers6.3%
  • Bayesian Methods and Mixture Models4%
  • Immunotherapy and Immune Responses3.2%
  • Statistical Methods and Inference3.1%
  • Immune Cell Function and Interaction2%
  • Esophageal Cancer Research and Treatment1.8%
  • Other79.6%

Coauthors

All papers

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  1. RANDOM SURVIVAL FORESTS

    Authors: , , , - The Annals of Applied Statistics 2008 cited by 2,449

  2. Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade

    Authors: , , , , , , , , , , , , , , , , , , - Cell 2016 cited by 1,194

  3. Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , - Nature 2015 cited by 2,431

  4. Random forest missing data algorithms

    Authors: , - Statistical Analysis and Data Mining The ASA Data Science Journal, Stat. Anal. Data Min. 2017 cited by 776

  5. Opposing Functions of Interferon Coordinate Adaptive and Innate Immune Responses to Cancer Immune Checkpoint Blockade

    Authors: , , , , , , , , , , , , , , , , - Cell 2019 cited by 563

  6. Random forests for genomic data analysis

    Authors: , - Genomics 2012 cited by 974

  7. Cancer of the Esophagus and Esophagogastric Junction: An Eighth Edition Staging Primer

    Authors: , , , , - Journal of Thoracic Oncology 2016 cited by 701

  8. An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer

    Authors: , , , , , , , , , , , , , , - National Academy of Sciences, Proceedings of the National Academy of Sciences 2008 cited by 622

  9. Exosome Transfer from Stromal to Breast Cancer Cells Regulates Therapy Resistance Pathways

    Authors: , , , , , , , , , , , , , - Cell 2014 cited by 804

  10. Spike and slab variable selection: Frequentist and Bayesian strategies

    Authors: , - The Annals of Statistics 2005 cited by 1,076

  11. Cancer cells resistant to immune checkpoint blockade acquire interferon-associated epigenetic memory to sustain T cell dysfunction

    Authors: , , , , , , , , , , , - Nature Cancer 2023 cited by 102

  12. Evaluating Random Forests for Survival Analysis Using Prediction Error Curves

    Authors: , , - Journal of Statistical Software 2012 cited by 455

  13. Gibbs Sampling Methods for Stick-Breaking Priors

    Authors: , - Journal of the American Statistical Association 2001 cited by 1,556

  14. High-Dimensional Variable Selection for Survival Data

    Authors: , , , , - Journal of the American Statistical Association 2010 cited by 454

  15. Random survival forests for competing risks

    Authors: , , , , , - Biostatistics 2014 cited by 291

  16. Random survival forests for high-dimensional data

    Authors: , , , - Statistical Analysis and Data Mining The ASA Data Science Journal, Stat. Anal. Data Min. 2011 cited by 219

  17. Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival

    Authors: , - Statistics in Medicine 2018 cited by 268

  18. Variable importance in binary regression trees and forests

    Authors: - Electronic Journal of Statistics 2007 cited by 396

  19. The effect of splitting on random forests

    Authors: - Machine Learning, Mach. Learn. 2014 cited by 231

  20. A random forests quantile classifier for class imbalanced data

    Authors: , - Pattern Recognition, Pattern Recognit. 2019 cited by 176

  21. Consistency of random survival forests

    Authors: , - Statistics & Probability Letters 2010 cited by 286

  22. Recommendations for pathologic staging (pTNM) of cancer of the esophagus and esophagogastric junction for the 8th edition AJCC/UICC staging manuals

    Authors: , , , , , - Diseases of the Esophagus 2016 cited by 279

  23. Unsupervised random forests

    Authors: , - Statistical Analysis and Data Mining The ASA Data Science Journal, Stat. Anal. Data Min. 2021 cited by 46

  24. Identifying Important Risk Factors for Survival in Patient With Systolic Heart Failure Using Random Survival Forests

    Authors: , , , , - Circulation Cardiovascular Quality and Outcomes 2010 cited by 173