Loza Lab

Research

Focus areas, open-source software, and selected publications.

Focus

The Loza Lab focuses on development of statistical and deep learning methods to leverage Real-World Data to improve clinical care with a focus on multimodal medical foundation models.

Predicting and simulating patient trajectories with longitudinal models
Predictive models that connect the right inputs, model, and delivery into clinical workflow
Scale and collaboration across Yale and the VA Connecticut Healthcare System
Foundation models and generative methods for multimodal clinical data

Software

Open-source repositories for mixed-type sequence modeling and medical data tokenization.

multivariategpt

A decoder-only transformer for mixed categorical and numeric data: categorical inputs behave like language-model tokens, while numeric values use a modified embedding and loss so continuous quantities stay continuous (no discretization). Joint modeling of token class and value extends next-token prediction to mixed sequences, relevant for EHR time series and other irregular multivariate streams.

GitHubPaper (arXiv)

dbtoken

A tokenizer for long-format EHR and database tables. Converts structured clinical records into dense token sequences for autoregressive models, with concept or BPE text modes and discrete or continuous numeric values.

GitHubDemoPyPI

medspipeline

Python tools to transform wide tabular clinical data into long-format MEDS (Medical Event Data Standard) tables, choose distributions for scaling, and tokenize for medical foundation models, including a path to train multivariateGPT on tokenized data.

GitHub

Selected papers

For the full publication list and citation metrics, see Google Scholar.

  • Continuous Value Tokenization Improves Medical Event Foundation Models

    Kent A. McCann, Ikgyu Shin, Huan Li, Davis White, Edward R. Melnick, Mark Iscoe, Andrew J. Loza

    medRxiv, 2026

    medRxivPDF

  • Post-ED Trajectory Prediction in Abdominal Pain with a Generative Medical Event Model

    Kent A. McCann, Donald S. Wright, Mark Iscoe, Edward R. Melnick, Lucila Ohno-Machado, Daniella Meeker, Arjun K. Venkatesh, Rohit B. Sangal, Andrew J. Loza

    medRxiv, 2026

    medRxivPDF

  • Conditional Attribute Estimation with Autoregressive Sequence Models

    Erica Stutz, Giacomo Marino, Daniella Meeker, Qiao Liu, Andrew J. Loza

    arXiv preprint, 2026

    arXivPDFDemo

  • multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data

    Andrew J. Loza, Jun Yup Kim, Shangzheng Song, Yihang Liu, Joseph J. Y. Sung, R Andrew Taylor, Dennis L. Shung

    arXiv preprint, 2025

    arXivPDFGitHub

All publications on Google Scholar

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