| 1 | Disease diagnostics using machine learning of B cell and T cell receptor sequences | 38.2 | 2 | Citations (PDF) |
| 2 | Artificial Intelligence Identifies Factors Associated with Blood Loss and Surgical Experience in Cholecystectomy 2024, 1, | | 4 | Citations (PDF) |
| 3 | A tissue atlas of ulcerative colitis revealing evidence of sex-dependent differences in disease-driving inflammatory cell types and resistance to TNF inhibitor therapy | 11.3 | 17 | Citations (PDF) |
| 4 | Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank | 2.1 | 24 | Citations (PDF) |
| 5 | Prediction and Outlier Detection in Classification Problems | 2.9 | 14 | Citations (PDF) |
| 6 | Significant sparse polygenic risk scores across 813 traits in UK Biobank | 3.3 | 52 | Citations (PDF) |
| 7 | What is Cox's proportional hazards model? | 0.3 | 1 | Citations (PDF) |
| 8 | ARTERIAL THROMBOSIS- A COMPLICATION OF COVID-19 PNEUMONIA: A CASE SERIES REPORT 2022, , 49-52 | | 0 | Citations (PDF) |
| 9 | Increased diversity of gut microbiota during active oral immunotherapy in peanut‐allergic adults | 7.6 | 22 | Citations (PDF) |
| 10 | Genetics of 35 blood and urine biomarkers in the UK Biobank | 16.3 | 388 | Citations (PDF) |
| 11 | Polygenic risk modeling with latent trait-related genetic components | 3.1 | 10 | Citations (PDF) |
| 12 | Assessment of heterogeneous treatment effect estimation accuracy via matching | 1.7 | 5 | Citations (PDF) |
| 13 | Principal component‐guided sparse regression | 0.8 | 6 | Citations (PDF) |
| 14 | MassExplorer: a computational tool for analyzing desorption electrospray ionization mass spectrometry data | 5.0 | 4 | Citations (PDF) |
| 15 | Fast numerical optimization for genome sequencing data in population biobanks | 5.0 | 10 | Citations (PDF) |
| 16 | De novo mutational signature discovery in tumor genomes using SparseSignatures | 3.3 | 18 | Citations (PDF) |
| 17 | The stanford prostate cancer calculator: Development and external validation of online nomograms incorporating PIRADS scores to predict clinically significant prostate cancer | 1.9 | 16 | Citations (PDF) |
| 18 | Penalized regression for left‐truncated and right‐censored survival data | 1.7 | 29 | Citations (PDF) |
| 19 | An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging | 8.5 | 263 | Citations (PDF) |
| 20 | Using Aggregate Patient Data at the Bedside via an On-Demand Consultation Service | 0.9 | 8 | Citations (PDF) |
| 21 | Can auxiliary indicators improve COVID-19 forecasting and hotspot prediction? | 7.7 | 31 | Citations (PDF) |
| 22 | An open repository of real-time COVID-19 indicators | 7.7 | 32 | Citations (PDF) |
| 23 | Main Effects and Interactions in Mixed and Incomplete Data Frames | 3.5 | 12 | Citations (PDF) |
| 24 | A Pliable Lasso | 2.0 | 20 | Citations (PDF) |
| 25 | Identification of diagnostic metabolic signatures in clear cell renal cell carcinoma using mass spectrometry imaging | 4.5 | 45 | Citations (PDF) |
| 26 | Integration of mechanistic immunological knowledge into a machine learning pipeline improves predictions | 17.4 | 55 | Citations (PDF) |
| 27 | Transcriptional changes in peanut-specific CD4+ T cells over the course of oral immunotherapy | 2.2 | 27 | Citations (PDF) |
| 28 | Reluctant Generalised Additive Modelling | 2.3 | 8 | Citations (PDF) |
| 29 | Defining the features and duration of antibody responses to SARS-CoV-2 infection associated with disease severity and outcome | 14.0 | 344 | Citations (PDF) |
| 30 | Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron | 3.5 | 0 | Citations (PDF) |
| 31 | Origins and clonal convergence of gastrointestinal IgE
<sup>+</sup>
B cells in human peanut allergy | 14.0 | 105 | Citations (PDF) |
| 32 | Integrating genomic features for non-invasive early lung cancer detection | 40.1 | 453 | Citations (PDF) |
| 33 | Post model‐fitting exploration via a “Next‐Door” analysis | 0.8 | 4 | Citations (PDF) |
| 34 | Metabolic Dynamics and Prediction of Gestational Age and Time to Delivery in Pregnant WomenCell, 2020, 181, 1680-1692.e15 | 35.1 | 177 | Citations (PDF) |
| 35 | Discussion of “Prediction, Estimation, and Attribution” by Bradley Efron | 2.3 | 2 | Citations (PDF) |
| 36 | A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank | 3.3 | 64 | Citations (PDF) |
| 37 | Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy | 5.0 | 140 | Citations (PDF) |
| 38 | Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome PredictionCell, 2019, 178, 699-713.e19 | 35.1 | 151 | Citations (PDF) |
| 39 | Sustained outcomes in oral immunotherapy for peanut allergy (POISED study): a large, randomised, double-blind, placebo-controlled, phase 2 study | 35.3 | 244 | Citations (PDF) |
| 40 | Reply to J. Wang et al | 17.1 | 2 | Citations (PDF) |
| 41 | Shaping of infant B cell receptor repertoires by environmental factors and infectious disease | 13.1 | 51 | Citations (PDF) |
| 42 | Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells | 18.1 | 41 | Citations (PDF) |
| 43 | Log-Ratio Lasso: Scalable, Sparse Estimation for Log-Ratio Models | 1.7 | 22 | Citations (PDF) |
| 44 | Some methods for heterogeneous treatment effect estimation in high dimensions | 1.7 | 95 | Citations (PDF) |
| 45 | Single-cell developmental classification of B cell precursor acute lymphoblastic leukemia at diagnosis reveals predictors of relapse | 25.6 | 95 | Citations (PDF) |
| 46 | Genomic feature selection by coverage design optimization | 1.6 | 1 | Citations (PDF) |
| 47 | A proteomic clock of human pregnancy | 2.5 | 81 | Citations (PDF) |
| 48 | Food allergy and omics | 2.8 | 60 | Citations (PDF) |
| 49 | A General Framework for Estimation and Inference From Clusters of Features | 3.5 | 11 | Citations (PDF) |
| 50 | Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma | 17.1 | 337 | Citations (PDF) |
| 51 | Multicenter Study Using Desorption-Electrospray-Ionization-Mass-Spectrometry Imaging for Breast-Cancer Diagnosis | 6.7 | 73 | Citations (PDF) |
| 52 | Landscape of monoallelic DNA accessibility in mouse embryonic stem cells and neural progenitor cells | 16.3 | 65 | Citations (PDF) |
| 53 | Long-term course of patients with primary ocular adnexal MALT lymphoma: a large single-institution cohort studyBlood, 2017, 129, 324-332 | 1.0 | 62 | Citations (PDF) |
| 54 | Chemical Space Mimicry for Drug Discovery | 4.9 | 65 | Citations (PDF) |
| 55 | Metabolic Markers and Statistical Prediction of Serous Ovarian Cancer Aggressiveness by Ambient Ionization Mass Spectrometry Imaging | 0.6 | 98 | Citations (PDF) |
| 56 | An immune clock of human pregnancy | 14.0 | 344 | Citations (PDF) |
| 57 | Post‐selection point and interval estimation of signal sizes in Gaussian samples | 0.8 | 12 | Citations (PDF) |
| 58 | Development of a Dynamic Model for Personalized Risk Assessment in Large B-Cell LymphomaBlood, 2017, 130, 826-826 | 1.0 | 4 | Citations (PDF) |
| 59 | Sparse regression and marginal testing using cluster prototypes | 2.1 | 14 | Citations (PDF) |
| 60 | Noninvasive Cancer Classification Using Diverse Genomic Features in Circulating Tumor DNA 2016, , 516-516 | | 0 | Citations (PDF) |
| 61 | Pathophysiological significance and therapeutic targeting of germinal center kinase in diffuse large B-cell lymphomaBlood, 2016, 128, 239-248 | 1.0 | 17 | Citations (PDF) |
| 62 | Data Shared Lasso: A novel tool to discover uplift | 1.5 | 25 | Citations (PDF) |
| 63 | Customized training with an application to mass spectrometric imaging of cancer tissue | 1.2 | 9 | Citations (PDF) |
| 64 | Collaborative regression | 2.1 | 48 | Citations (PDF) |
| 65 | Pancancer analysis of DNA methylation-driven genes using MethylMix | 14.0 | 100 | Citations (PDF) |
| 66 | Quantitative SD-OCT Imaging Biomarkers as Indicators of Age-Related Macular Degeneration Progression 2014, 55, 7093 | | 115 | Citations (PDF) |
| 67 | Increasing value and reducing waste in research design, conduct, and analysis | 35.3 | 1,169 | Citations (PDF) |
| 68 | A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates | 3.5 | 227 | Citations (PDF) |
| 69 | A significance test for the lasso | 2.7 | 376 | Citations (PDF) |
| 70 | A Sparse-Group Lasso | 2.0 | 956 | Citations (PDF) |
| 71 | Sensitivity analysis for inference with partially identifiable covariance matrices | 1.2 | 1 | Citations (PDF) |
| 72 | Standardization and the Group Lasso Penalty | 0.4 | 87 | Citations (PDF) |
| 73 | Inference with Transposable Data: Modelling the Effects of Row and Column Correlations | 2.9 | 25 | Citations (PDF) |
| 74 | Hierarchical Clustering With Prototypes via Minimax Linkage | 3.5 | 130 | Citations (PDF) |
| 75 | Nearly-Isotonic Regression | 3.0 | 66 | Citations (PDF) |
| 76 | Gene expression deconvolution in linear space | 14.5 | 5 | Citations (PDF) |
| 77 | Reply to D.R. Catchpoole et al | 17.1 | 1 | Citations (PDF) |
| 78 | Transposable regularized covariance models with an application to missing data imputation | 1.2 | 80 | Citations (PDF) |
| 79 | Discussion | 3.5 | 1 | Citations (PDF) |
| 80 | MicroRNA Are Useful Biomarkers for Prediction of Response to Therapy and Survival of Patients with Diffuse Large B-Cell Lymphoma.Blood, 2009, 114, 624-624 | 1.0 | 1 | Citations (PDF) |
| 81 | Differentiation-Stage-Specific Expression of MicroRNAs in B-Lymphocytes and Diffuse Large B-Cell Lymphomas (DLBCL)Blood, 2008, 112, 805-805 | 1.0 | 12 | Citations (PDF) |
| 82 | Neither CD68+ Nor CD163+ Macrophages Are Associated with Decreased Survival in Follicular LymphomaBlood, 2008, 112, 3747-3747 | 1.0 | 0 | Citations (PDF) |
| 83 | Lymphoma-Expressed VEGF-a, VEGFR-1, VEGFR-2, and Microvessel Density Are Not Predictive of Overall Survival in Follicular LymphomaBlood, 2008, 112, 3767-3767 | 1.0 | 0 | Citations (PDF) |
| 84 | Survival in Follicular Lymphoma: The Stanford Experience, 1960–2003.Blood, 2007, 110, 3428-3428 | 1.0 | 6 | Citations (PDF) |
| 85 | LMO2 Protein Expression Predicts Survival in Patients with Diffuse Large B-Cell Lymphoma in the Pre- and Post-Rituximab Treatment Eras. | 1.0 | 2 | Citations (PDF) |
| 86 | Anti-Idiotype Antibody Response after Vaccination Correlates with Better Overall Survival in Follicular Lymphoma.Blood, 2007, 110, 647-647 | 1.0 | 0 | Citations (PDF) |
| 87 | Sparse Principal Component Analysis | 2.0 | 2,108 | Citations (PDF) |
| 88 | Prediction by Supervised Principal Components | 3.5 | 534 | Citations (PDF) |
| 89 | Comment | 3.5 | 0 | Citations (PDF) |
| 90 | Cluster Validation by Prediction Strength | 2.0 | 412 | Citations (PDF) |
| 91 | Least angle regression | 2.7 | 6,447 | Citations (PDF) |
| 92 | Diagnosis of multiple cancer types by shrunken centroids of gene expression | 7.7 | 2,324 | Citations (PDF) |
| 93 | Empirical Bayes Analysis of a Microarray Experiment | 3.5 | 1,275 | Citations (PDF) |
| 94 | Estimating the Number of Clusters in a Data Set Via the Gap Statistic | 2.9 | 4,015 | Citations (PDF) |
| 95 | Statistical Measures for the Computer-Aided Diagnosis of Mammographic Masses | 2.0 | 2 | Citations (PDF) |
| 96 | Model Search by Bootstrap “Bumping” | 2.0 | 28 | Citations (PDF) |
| 97 | A comparison of statistical learning methods on the GUSTO database 1998, 17, 2501-2508 | | 67 | Citations (PDF) |
| 98 | Who is the Fastest Man in the World? | 1.6 | 13 | Citations (PDF) |
| 99 | Impact of menstrual phase on false-negative mammograms in the canadian national breast screening study | 4.4 | 56 | Citations (PDF) |
| 100 | THE LASSO METHOD FOR VARIABLE SELECTION IN THE COX MODEL | 1.7 | 2,922 | Citations (PDF) |
| 101 | Regression Shrinkage and Selection Via the Lasso | 2.9 | 30,230 | Citations (PDF) |
| 102 | A Comparison of Some Error Estimates for Neural Network Models | 2.2 | 200 | Citations (PDF) |
| 103 | Combining Estimates in Regression and Classification | 3.5 | 166 | Citations (PDF) |
| 104 | Flexible Discriminant Analysis by Optimal Scoring | 3.5 | 568 | Citations (PDF) |
| 105 | Adaptive Principal Surfaces | 3.5 | 78 | Citations (PDF) |
| 106 | Flexible Discriminant Analysis by Optimal Scoring | 3.5 | 144 | Citations (PDF) |
| 107 | Adaptive Principal Surfaces | 3.5 | 25 | Citations (PDF) |
| 108 | A Strategy for Binary Description and Classification | 2.0 | 4 | Citations (PDF) |
| 109 | Estimating Transformations for Regression via Additivity and Variance Stabilization | 3.5 | 150 | Citations (PDF) |
| 110 | Estimating Transformations for Regression Via Additivity and Variance Stabilization | 3.5 | 36 | Citations (PDF) |
| 111 | Comment | 3.5 | 0 | Citations (PDF) |
| 112 | Bootstrap Confidence Intervals and Bootstrap Approximations | 3.5 | 70 | Citations (PDF) |
| 113 | Local Likelihood Estimation | 3.5 | 359 | Citations (PDF) |
| 114 | Generalized Additive Models: Some Applications | 3.5 | 632 | Citations (PDF) |
| 115 | Bootstrap Confidence Intervals and Bootstrap Approximations | 3.5 | 13 | Citations (PDF) |
| 116 | Generalized Additive Models: Some Applications | 3.5 | 70 | Citations (PDF) |
| 117 | Local Likelihood Estimation | 3.5 | 92 | Citations (PDF) |
| 118 | The Bootstrap Method for Assessing Statistical Accuracy | 0.9 | 150 | Citations (PDF) |
