MIBoost extends gradient boosting to multiple imputation by defining a single loss function that produces one set of selected variables across all imputed datasets.
mice: Multivariate Imputation by Chained Equations in R
6 Pith papers cite this work. Polarity classification is still indexing.
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ClusterChirp is a freely available web tool for scalable interactive visualization, hierarchical clustering, and natural-language-guided analysis of high-dimensional omics datasets.
SPICE is a scalable Bayesian MCMC engine for explanatory IRT calibration on sparsely linked persons and items in large assessment banks.
Football fever in spectators follows a V-shaped time course captured as a latent process from heart rate and stress data via time-dependent structural equation modeling.
A fine-tuned deep learning model using systemic EHR data achieved AUROC 0.883 and PPV 0.657 for identifying glaucoma in a held-out Stanford cohort of over 20,000 patients.
Machine learning models trained on Bangladeshi community data achieve 89-90% balanced accuracy for early CKD detection using few accessible features, outperforming traditional screening tools and generalizing across external datasets from India, UAE, and Bangladesh.
citing papers explorer
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MIBoost: A gradient boosting algorithm for variable selection after multiple imputation
MIBoost extends gradient boosting to multiple imputation by defining a single loss function that produces one set of selected variables across all imputed datasets.
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ClusterChirp: Scalable Interactive Exploration of Omics Data with Natural Language-Guided Analysis
ClusterChirp is a freely available web tool for scalable interactive visualization, hierarchical clustering, and natural-language-guided analysis of high-dimensional omics datasets.
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A Scalable Parametric Item Calibration Engine (SPICE) for Explanatory IRT with Sparse Data
SPICE is a scalable Bayesian MCMC engine for explanatory IRT calibration on sparsely linked persons and items in large assessment banks.
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Time-dependent structural equation modeling of fans' football fever using activity tracking data during the 2025 DFB Cup final
Football fever in spectators follows a V-shaped time course captured as a latent process from heart rate and stress data via time-dependent structural equation modeling.
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Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records
A fine-tuned deep learning model using systemic EHR data achieved AUROC 0.883 and PPV 0.657 for identifying glaucoma in a held-out Stanford cohort of over 20,000 patients.
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Community-Based Early-Stage Chronic Kidney Disease Screening using Explainable Machine Learning for Low-Resource Settings
Machine learning models trained on Bangladeshi community data achieve 89-90% balanced accuracy for early CKD detection using few accessible features, outperforming traditional screening tools and generalizing across external datasets from India, UAE, and Bangladesh.