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穆罕默德·本·扎耶德人工智能大学 数字生物统计学 Marcos Matabuena 研究组

研究

正在到来的未来

设想一个人独自在家发生急性冠状动脉综合征，身上佩戴着持续监测生命体征的设备。当设备检测到心电图异常或血氧下降等关键变化时，便自动触发急救响应。数秒内，系统定位并派出最近的可用救护车，同时根据交通状况和医院接诊能力等因素实时调整。

在转运途中，设备持续传输患者的重要数据，从而动态调整 医疗 和后勤决策。如果患者病情恶化，医院会收到警报，提前准备重症监护单元。抵达医院后，预测模型辅助决策，力求获得最佳救治结果，同时提高医疗资源的使用效率。

我们的使命与愿景

我们的长期目标是结合生物统计学、数字健康技术与运筹学，建立医疗卫生决策框架，支持个体和人群层面更好的临床与公共卫生决策。

智能手机数据缺失示意动画

我们正在为涉及连续、高频和实时健康数据的复杂临床问题开发统计与人工智能方法。我们希望这些方法不仅能回答现有医学问题，还能帮助识别最值得研究的问题：什么饮食最适合某个具体的人？需要多少体力活动才能促进健康老龄化与长寿？这些建议应如何根据个体的临床特征、生物学特征、环境与生活方式进行调整？

为回答这些问题，我们整合用于因果推断、生存分析、不确定性量化及随机效应生成建模的现代统计人工智能方法，推进非欧几里得随机对象的统计学习。周密的研究设计和计算可扩展性是这一愿景的重要基础。我们的目标是开发兼具数学严谨性与人群尺度计算效率的方法，面向 UK Biobank、All of Us Research Program、Human Phenotype Project 和 NHANES 等生物医学资源。

Human Phenotype Project

许多发表于顶级方法学期刊的方法虽然数学严谨、技术可靠，却未必充分考虑真实临床数据的复杂性及其分析假设。因此，我们以具体的生物医学问题和实践挑战为研究起点，开发能够体现数据结构、临床实践实际情况，以及患者、临床医生和卫生系统所面临关键决策的方法，推动领域发展。

数字健康研究计划的七大支柱

Glucodensities: A new representation of glucose profiles using distributional data analysis 的摘要

Glucodensities: A new representation of glucose profiles using distributional data analysis

Marcos Matabuena, Alexander Petersen, Juan C Vidal, Francisco Gude

我们的七篇论文为数字健康领域带来了重要的方法学与概念进展。

葡萄糖密度概念的提出，是通过函数型与分布型数据分析构建更复杂数字表型的第一步。这一框架为生物学发现开辟新方向，使我们能够更高效地利用新型医疗设备生成的连续信息，而非将这些数据压缩为少数几个标量指标。

多元葡萄糖密度的提出，是分析人体生理过程的又一概念进展。临床数据不再仅被视为单个数值，而是更接近医学影像的复杂对象。我们由此能够将潜在生理过程的动态特征整合进统一的葡萄糖密度分布框架。

与 Ciprian Crainiceanu 合作开展的葡萄糖密度随机效应模型研究，将这些思想扩展到持续数周、数月或数年的纵向研究。这项工作为临床试验使用数字信息建立了新框架，有望提高统计功效，并发现更具意义的新型纵向生物标志物。

与 Mateo Cámara合作，我们提出了首个一般度量空间中的随机效应建模框架，为分析临床研究中不同类型的统计对象提供统一方法。数字健康采集的信息大多在时间上近乎连续、涉及多个时间尺度，并自然呈现多层结构。我们的框架首次提供了在更广泛数学条件下对这些复杂变异来源进行建模的一般分析方法。

我们与 Gábor Lugosi共同开发的度量空间不确定性量化框架具有重要方法学意义：它提供了一种无需苛刻光滑性条件即可校准和评估条件覆盖率的形式化方法。同时，它为未来生物标志物的不确定性量化建立了更一般的框架，因为这些标志物将越来越多地表示为分布、函数、图像、网络或其他复杂的非欧几里得随机对象。

我们与中国同事 Mingyang Yi, Zhiming Ma以及 Ruoyu Wang在扩散模型与测量误差方面的合作，为将测量不确定性纳入生物医学决策创造了可能。其核心思想是将通用生成式人工智能方法嵌入经典测量误差统计流程，从而把传感器、临床测量及其他生物医学技术产生的误差直接纳入分析。

最后，数据驱动新时代的成功也取决于新型实验与抽样设计的发展。我们与 Yating Zou 与 Michael Kosorok共同提出了一种面向复杂抽样调查数据的新型随机森林方法。该方法在节点层面实施自助法，具有重要的推断意义。这为提升复杂抽样设计下机器学习方法的表现提供了新的理论机会，同时为利用大型健康数据集、保持对目标人群有效的统计推断提供了有理论依据的途径。

这些研究共同构成了我们研究计划的主要支柱：数字健康数据的新型表示、纵向与多层建模、不确定性量化、生成式人工智能驱动的测量误差校正，以及复杂生物医学研究中的有效统计推断。

往年研究成果

2026

Denoising Data with Measurement Error Using a Reproducing Kernel-based Diffusion Model
Denoising Data with Measurement Error Using a Reproducing Kernel-based Diffusion Model
Mingyang Yi, Marcos Matabuena, Zhiming Ma, Ruoyu Wang
arXiv  ·  14 Jul 2026  ·  arxiv:2501.00212
EpiBinder: a multimodal framework for cell-type-specific prediction and interpretation of transcription factor binding
EpiBinder: a multimodal framework for cell-type-specific prediction and interpretation of transcription factor binding
Ruben Solozabal, Albert Baichorov, Irina Miodownik, Tamir Avioz, Le Song, Marcos Matabuena, Martin Takáč, Ariel Afek
openRxiv  ·  08 Jul 2026  ·  10.64898/2026.07.06.736502
Pre-activity glycemic prediction prioritizes post-meal movement
Pre-activity glycemic prediction prioritizes post-meal movement
Smadar Shilo, Gal Sapir, Guy Lutsker, Yeela Talmor-Barkan, Anastasia Godneva, Alon Diament, Marcos Matabuena, Eran Segal, Hagai Rossman
openRxiv  ·  24 Jun 2026  ·  doi:10.64898/2026.06.22.26356272
Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
Gábor Lugosi, Marcos Matabuena
arXiv  ·  23 Jun 2026  ·  arxiv:2507.15741
A Deep Learning-Based Predictive Algorithm for Metabolic Syndrome Detection in the U.S. Population
A Deep Learning-Based Predictive Algorithm for Metabolic Syndrome Detection in the U.S. Population
Cristina Correa, Ruben Solozabal, Ziad Akram Ali Hammouri, Fernando Gómez-Peralta, Hagai Rossman, Juan C. Vidal, David C. Klonoff, Eran Segal, Marcos Matabuena
openRxiv  ·  02 Jun 2026  ·  doi:10.64898/2026.05.24.26354007
Capturing the Curve: Functional Data Analysis for Validated Digital Outcome Measures
Capturing the Curve: Functional Data Analysis for Validated Digital Outcome Measures
Mia S. Tackney, Marcos Matabuena, Marco Palma, Michael Wester, Claire Maassen, Thomas Krammer, Julian Mustroph, Peter H. Charlton, James Carpenter, Sofia S. Villar
arXiv  ·  28 May 2026  ·  arxiv:2605.28344
Gaussian mixture models in Hilbert spaces via kernel methods
Gaussian mixture models in Hilbert spaces via kernel methods
Daniel López-Montero, Antonio Álvarez-López, Marcos Matabuena
arXiv  ·  08 May 2026  ·  arxiv:2605.05996
Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs
Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs
Marcos Matabuena, Juan C Vidal, Rahul Ghosal, Jukka-Pekka Onnela
Statistical Methods in Medical Research  ·  07 May 2026  ·  doi:10.1177/09622802261442893
Random-Effects Algorithm for Random Objects in Metric Spaces
Random-Effects Algorithm for Random Objects in Metric Spaces
Marcos Matabuena, Mateo Cámara
arXiv  ·  05 May 2026  ·  arxiv:2605.02693
Continuous-Time Learning of Probability Distributions: A Case Study in a Digital Trial of Young Children with Type 1 Diabetes
Continuous-Time Learning of Probability Distributions: A Case Study in a Digital Trial of Young Children with Type 1 Diabetes
Antonio Álvarez-López, Marcos Matabuena
arXiv  ·  26 Mar 2026  ·  arxiv:2603.24427
Multilevel functional distributional models with applications to continuous glucose monitoring in diabetes clinical trials
Multilevel functional distributional models with applications to continuous glucose monitoring in diabetes clinical trials
Marcos Matabuena, Ciprian M. Crainiceanu
The Annals of Applied Statistics  ·  01 Mar 2026  ·  doi:10.1214/26-AOAS2139
Glucodensity-Based Models Outperform Time in Range and Glycemia Risk Index in Prediction Models
Glucodensity-Based Models Outperform Time in Range and Glycemia Risk Index in Prediction Models
Mandy M. Shao, Agatha F. Scheideman, David C. Klonoff, Francisco Gude, Marcos Matabuena
Journal of Diabetes Science and Technology  ·  23 Feb 2026  ·  doi:10.1177/19322968261421954
Survival on Image Regression With Application to Partially Functional Distributional Representation of Physical Activity
Survival on Image Regression With Application to Partially Functional Distributional Representation of Physical Activity
Rahul Ghosal, Sunwoo Emma Cho, Marcos Matabuena
Statistical Analysis and Data Mining: An ASA Data Science Journal  ·  01 Feb 2026  ·  doi:10.1002/sam.70068
Exploratory analysis of smartphone-based step counts as a digital biomarker for survival in ALS patients
Exploratory analysis of smartphone-based step counts as a digital biomarker for survival in ALS patients
Marcos Matabuena, Marcin Straczkiewicz, Narghes Calcagno, Katherine M. Burke, Timothy B. Royse, Amrita Iyer, Kendall T. Carney, Sydney Hall, James D. Berry, Jukka-Pekka Onnela
Frontiers in Digital Health  ·  29 Jan 2026  ·  doi:10.3389/fdgth.2025.1705368
Beyond scalar metrics: functional data analysis of postprandial continuous glucose monitoring in the AEGIS study
Beyond scalar metrics: functional data analysis of postprandial continuous glucose monitoring in the AEGIS study
Marcos Matabuena, Joseph Sartini, Francisco Gude
BMC Medical Research Methodology  ·  24 Jan 2026  ·  doi:10.1186/s12874-025-02748-2
Distributional Random Forests for Complex Survey Designs on Reproducing Kernel Hilbert Spaces
Distributional Random Forests for Complex Survey Designs on Reproducing Kernel Hilbert Spaces
Yating Zou, Marcos Matabuena, Michael R. Kosorok
arXiv  ·  07 Jan 2026  ·  arxiv:2512.08179
Daily Physical Activity Patterns Enhance Mortality Prediction in NHANES 2011-2014: A Comparative Study Across Classical, Machine Learning, and Deep Learning Models Using Accelerometer Data
Daily Physical Activity Patterns Enhance Mortality Prediction in NHANES 2011-2014: A Comparative Study Across Classical, Machine Learning, and Deep Learning Models Using Accelerometer Data
Srimanta Ghosh, Sunwoo Emma Cho, Yuanzhen Yue, Marcos Matabuena, Enakshi Saha, Rahul Ghosal
Journal for the Measurement of Physical Behaviour  ·  01 Jan 2026  ·  doi:10.1123/jmpb.2025-0052
From Physical Activity to Spirometry as a Curve : A Combined Model for Mortality Prediction
From Physical Activity to Spirometry (as a Curve): A Combined Model for Mortality Prediction
Marcos Matabuena, Marcos Matabuena@mbzuai Ac Ae, Emma Cho, Rahul Ghosal, Cristina Correa, Mateo Cámara, Manuel Oviedo De La Fuente, Holger Cevallos, Francisco Gude
未发表  ·  01 Jan 2026  ·  doi:10.13140/RG.2.2.35806.60486

2025

Continuous Glucose Monitoring as an alternative for Cystic Fibrosis Related diabetes screening and diagnosis
Continuous Glucose Monitoring as an alternative for Cystic Fibrosis Related diabetes screening and diagnosis
I. Aguilera García, P. Vázquez Pérez, B. López Plaza, M. Matabuena, R.M. García Moreno, S.Palma Milla, E. Zamarrón de Lucas, M.C. Prados Sánchez, N. González Pérez de Villar
Diabetes Research and Clinical Practice  ·  01 Nov 2025  ·  doi:10.1016/j.diabres.2025.112952
Unequal strides to longevity. The extra mile to health equity
Unequal strides to longevity. The extra mile to health equity
Borja del Pozo Cruz, Francisco Perales, Marcin Straczkiewicz, Marcos Matabuena, Jesús del Pozo-Cruz, Rubén López-Bueno
Annals of Epidemiology  ·  01 Nov 2025  ·  doi:10.1016/j.annepidem.2025.10.009
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection
Marcos Matabuena, Juan C. Vidal, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
arXiv  ·  28 Oct 2025  ·  arxiv:2402.01635
Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models
Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models
Rahul Ghosal, Marcos Matabuena, Enakshi Saha
arXiv  ·  24 Oct 2025  ·  arxiv:2505.05416
ROC Analysis with Covariate Adjustment Using Neural Network Models: Evaluating the Role of Age in the Physical Activity-Mortality Association
ROC Analysis with Covariate Adjustment Using Neural Network Models: Evaluating the Role of Age in the Physical Activity-Mortality Association
Ziad Akram Ali Hammouri, Yating Zou, Rahul Ghosal, Juan C. Vidal, Marcos Matabuena
arXiv  ·  20 Oct 2025  ·  arxiv:2510.14494
Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics
Glucodensity functional profiles outperform traditional continuous glucose monitoring metrics
Marcos Matabuena, Rahul Ghosal, Javier Enrique Aguilar, Ayya Keshet, Robert Wagner, Carmen Fernández Merino, Juan Sánchez Castro, Vadim Zipunnikov, Jukka-Pekka Onnela, Francisco Gude
Scientific Reports  ·  29 Sep 2025  ·  doi:10.1038/s41598-025-18119-2
Age, Sex, BMI, Meal Timing, and Glycemic Response to Meal Glycemic Load
Age, Sex, BMI, Meal Timing, and Glycemic Response to Meal Glycemic Load
Mar Calvo-Malvar, Óscar Lado-Baleato, Ana Cao Ríos, Cristina Porca Fernández, Alfonso Benítez-Calvo, Carmen Fernandez-Merino, Juan Sánchez-Castro, Robert Wagner, Marcos Matabuena, Francisco Gude
JAMA Network Open  ·  23 Sep 2025  ·  doi:10.1001/jamanetworkopen.2025.33193
Continuous Temporal Learning of Probability Distributions via Neural ODEs with Applications in Continuous Glucose Monitoring Data
Continuous Temporal Learning of Probability Distributions via Neural ODEs with Applications in Continuous Glucose Monitoring Data
Antonio Álvarez-López, Marcos Matabuena
arXiv  ·  18 Sep 2025  ·  arxiv:2505.08698
Distributional Data Analysis Uncovers Hundreds of Novel and Heritable Phenomic Features from Temporal Cotton and Maize Drone Imagery
Distributional Data Analysis Uncovers Hundreds of Novel and Heritable Phenomic Features from Temporal Cotton and Maize Drone Imagery
Aaron J. DeSalvio, Marcos Matabuena, Alper Adak, Mustafa A. Arik, Serina M. DeSalvio, …, Shawn M. Kaeppler, Dayane C. Lima, Candice N. Hirsch, Addie Thompson, David M. Stelly
openRxiv  ·  07 Sep 2025  ·  doi:10.1101/2025.09.05.674557
Functional time transformation model with applications to digital health
Functional time transformation model with applications to digital health
Rahul Ghosal, Marcos Matabuena, Sujit K. Ghosh
Computational Statistics & Data Analysis  ·  01 Jul 2025  ·  doi:10.1016/j.csda.2025.108131
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
arXiv  ·  11 Jun 2025  ·  arxiv:2506.08325
Conformal prediction for uncertainty quantification in dynamic biological systems
Conformal prediction for uncertainty quantification in dynamic biological systems
Alberto Portela, Julio R. Banga, Marcos Matabuena
PLOS Computational Biology  ·  12 May 2025  ·  doi:10.1371/journal.pcbi.1013098
A Telehealth Program Using Continuous Glucose Monitoring and a Connected Insulin Pen Cap in Nursing Homes for Older Adults with Insulin-Treated Diabetes: The Trescasas Study
A Telehealth Program Using Continuous Glucose Monitoring and a Connected Insulin Pen Cap in Nursing Homes for Older Adults with Insulin-Treated Diabetes: The Trescasas Study
Fernando Gomez-Peralta, Cristina Abreu, Estefanía Santos, Alvaro Da Silva, Ana San Frutos, …, Ana Franco-López, Cristina López Mardomingo, Benito Cañuelo, Guillermo Blazquez, Marcos Matabuena
Diabetes Technology & Therapeutics  ·  01 May 2025  ·  doi:10.1089/dia.2024.0356
Uncertainty quantification for intervals
Uncertainty quantification for intervals
Carlos García Meixide, Michael R. Kosorok, Marcos Matabuena
arXiv  ·  01 Apr 2025  ·  arxiv:2408.16381
Deep Learning Framework with Uncertainty Quantification for Survey Data: Assessing and Predicting Diabetes Mellitus Risk in the American Population
Deep Learning Framework with Uncertainty Quantification for Survey Data: Assessing and Predicting Diabetes Mellitus Risk in the American Population
Marcos Matabuena, Juan C. Vidal, Rahul Ghosal, Jukka-Pekka Onnela
arXiv  ·  27 Mar 2025  ·  arXiv:2403.19752
Optimal Cut-Point Estimation for Functional Digital Biomarkers: Application to Diabetes Risk Stratification via Continuous Glucose Monitoring
Optimal Cut-Point Estimation for Functional Digital Biomarkers: Application to Diabetes Risk Stratification via Continuous Glucose Monitoring
Oscar Lado-Baleato, Carla Díaz-Louza, Francisco Gude, Marcos Matabuena
arXiv  ·  11 Mar 2025  ·  arxiv:2404.09716
Causal survival embeddings: Non-parametric counterfactual inference under right-censoring
Causal survival embeddings: Non-parametric counterfactual inference under right-censoring
Carlos García Meixide, Marcos Matabuena
Statistical Methods in Medical Research  ·  11 Feb 2025  ·  doi:10.1177/09622802241311455
Kernel biclustering algorithm in Hilbert spaces
Kernel biclustering algorithm in Hilbert spaces
Marcos Matabuena, Juan C. Vidal, Oscar Hernan Madrid Padilla, Dino Sejdinovic
Advances in Data Analysis and Classification  ·  21 Jan 2025  ·  doi:10.1007/s11634-024-00619-0
Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age
Variable Selection Methods for Multivariate, Functional, and Complex Biomedical Data in the AI Age
Marcos Matabuena
arXiv  ·  14 Jan 2025  ·  arxiv:2501.06868

2024

Predicting distributions of physical activity profiles in the National Health and Nutrition Examination Survey database using a partially linear Fr chet single index model
Predicting distributions of physical activity profiles in the National Health and Nutrition Examination Survey database using a partially linear Fréchet single index model
Marcos Matabuena, Aritra Ghosal, Wendy Meiring, Alexander Petersen
Biostatistics  ·  31 Dec 2024  ·  doi:10.1093/biostatistics/kxaf013
Divergent hypoglycemic and hyperglycemic responses to the components of evening meals. A general adult population study in individuals without diabetes AEGIS Study
Divergent hypoglycemic and hyperglycemic responses to the components of evening meals. A general adult population study in individuals without diabetes (AEGIS Study)
Tomás González-Vidal, Mar Calvo-Malvar, Carmen Fernández-Merino, Juan Sánchez-Castro, Óscar Lado-Baleato, Carla Díaz-Louzao, Marcos Pazos-Couselo, Manuela Alonso-Sampedro, Marcos Matabuena, Francisco Gude
Clinical Nutrition  ·  01 Dec 2024  ·  doi:10.1016/j.clnu.2024.11.020
Exploring the Interplay Between Physical Activity, Dietary Patterns, Diabetes, and All-Cause Mortality in the U.S.A. Population, NHANES 2011-2014: A Distributional Data Analysis Perspective
Exploring the Interplay Between Physical Activity, Dietary Patterns, Diabetes, and All-Cause Mortality in the U.S.A. Population, NHANES 2011-2014: A Distributional Data Analysis Perspective
Marcos Matabuena, Anxo Carreira, Robert Wagner, Miguel Sousa, Miguel Saavedra, Rahul Ghosal, JP Onnela, Lucimere Bohn
Springer Science and Business Media LLC  ·  15 Nov 2024  ·  doi:10.21203/rs.3.rs-5314139/v1
Exploring the association between daily distributional patterns of physical activity and cardiovascular mortality risk among older adults in NHANES 2003-2006
Exploring the association between daily distributional patterns of physical activity and cardiovascular mortality risk among older adults in NHANES 2003-2006
Sunwoo Emma Cho, Enakshi Saha, Marcos Matabuena, Jingkai Wei, Rahul Ghosal
Annals of Epidemiology  ·  01 Nov 2024  ·  doi:10.1016/j.annepidem.2024.10.001
Uncertainty Quantification in Dynamic Models of Biological Systems Using Conformal Prediction
Uncertainty Quantification in Dynamic Models of Biological Systems Using Conformal Prediction
Alberto Portela, Julio R. Banga, Marcos Matabuena
[object Object]  ·  01 Oct 2024  ·  doi: 10.5281/zenodo.13838652
Book Review: Functional Data Analysis with R by Ciprian M. Crainiceanu, Jeff Goldsmith, Andrew Leroux, and Erjia Cui
Book Review: Functional Data Analysis with R by Ciprian M. Crainiceanu, Jeff Goldsmith, Andrew Leroux, and Erjia Cui
Marcos Matabuena
Journal of Agricultural, Biological and Environmental Statistics  ·  01 Oct 2024  ·  doi:10.1007/s13253-024-00656-4
Multivariate scalar on multidimensional distribution regression with application to modeling the association between physical activity and cognitive functions
Multivariate scalar on multidimensional distribution regression with application to modeling the association between physical activity and cognitive functions
Rahul Ghosal, Marcos Matabuena
Biometrical Journal  ·  22 Sep 2024  ·  doi:10.1002/bimj.202400042
Neural interval-censored survival regression with feature selection
Neural interval-censored survival regression with feature selection
Carlos García Meixide, Marcos Matabuena, Louis Abraham, Michael R. Kosorok
Statistical Analysis and Data Mining: The ASA Data Science Journal  ·  16 Jul 2024  ·  doi:10.1002/sam.11704
Energy Distance and Kernel Mean Embeddings for Two-Sample Survival Testing with Applications in Immunotherapy Clinical Trials
Energy Distance and Kernel Mean Embeddings for Two-Sample Survival Testing with Applications in Immunotherapy Clinical Trials
Marcos Matabuena, Oscar Hernan Madrid Padilla
REVSTAT-Statistical Journal  ·  14 Jun 2024  ·  doi:10.57805/revstat.vi.572
Conformal uncertainty quantification using kernel depth measures in separable Hilbert spaces
Conformal uncertainty quantification using kernel depth measures in separable Hilbert spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi, Oscar Hernan Madrid Padilla, Jukka-Pekka Onnela
arXiv  ·  24 May 2024  ·  arxiv:2405.13970
Uncertainty quantification in metric spaces
Uncertainty quantification in metric spaces
Gábor Lugosi, Marcos Matabuena
arXiv  ·  09 May 2024  ·  arxiv:2405.05110
Insulin glargine 300 U ml versus insulin degludec 100 U ml improves nocturnal glycaemic control and variability in type 1 diabetes under routine clinical practice: A glucodensities-based post hoc analysis of the OneCare study
Insulin glargine 300 U/ml versus insulin degludec 100 U/ml improves nocturnal glycaemic control and variability in type 1 diabetes under routine clinical practice: A glucodensities-based post hoc analysis of the OneCare study
Fernando Gomez‐Peralta, Ana Chico Ballesteros, Amparo Marco Martínez, Begoña Pérez Corral, Ignacio Conget Donlo, Paulina Fuentealba Melo, Fernando Zaragozá Arnáez, Marcos Matabuena Rodríguez
Diabetes, Obesity and Metabolism  ·  01 May 2024  ·  doi: 10.1111/dom.15496
Personalized Imputation in metric spaces via conformal prediction: Applications in Predicting Diabetes Development with Continuous Glucose Monitoring Information
Personalized Imputation in metric spaces via conformal prediction: Applications in Predicting Diabetes Development with Continuous Glucose Monitoring Information
Marcos Matabuena, Carla Díaz-Louzao, Rahul Ghosal, Francisco Gude
arXiv  ·  28 Mar 2024  ·  arxiv:2403.18069
Insulin glargine 300 U ml versus insulin degludec 100 U ml improves nocturnal glycaemic control and variability in type 1 diabetes under routine clinical practice: A glucodensities-based post hoc analysis of the OneCare study
Insulin glargine 300 U/ml versus insulin degludec 100 U/ml improves nocturnal glycaemic control and variability in type 1 diabetes under routine clinical practice: A glucodensities-based post hoc analysis of the OneCare study
Fernando Gomez‐Peralta, Ana Chico Ballesteros, Amparo Marco Martínez, Begoña Pérez Corral, Ignacio Conget Donlo, Paulina Fuentealba Melo, Fernando Zaragozá Arnáez, Marcos Matabuena Rodríguez
Diabetes, Obesity and Metabolism  ·  20 Feb 2024  ·  doi:10.1111/dom.15496
Author Correction: Reassessment of fluctuating dental asymmetry in Down syndrome
Author Correction: Reassessment of fluctuating dental asymmetry in Down syndrome
Marcos Matabuena Rodríguez, Pedro Diz Dios, Carmen Cadarso-Suárez, Márcio Diniz-Freitas, Mercedes Outumuro Rial, Maria Teresa Abeleira Pazos, Jacobo Limeres Posse
Scientific Reports  ·  16 Jan 2024  ·  doi:10.1038/s41598-024-51672-w

2021

Glucodensities: A new representation of glucose profiles using distributional data analysis
Glucodensities: A new representation of glucose profiles using distributional data analysis
Marcos Matabuena, Alexander Petersen, Juan C Vidal, Francisco Gude
Statistical Methods in Medical Research  ·  01 Jun 2021  ·  doi: 10.1177/0962280221998064