Faculty

Institution

Unit

Venue

Valentina Roquemen-Echeverri

Oregon Health & Science University

Affiliations

Department Of Artificial Intelligence For Medical Systems

NoneValentina Roquemen-echeverri is currently serving as a Artificial Intelligence For Medical Systems faculty at Oregon Health & Science University.

Honors

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Experiences

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Education

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Valentina Roquemen-Echeverri

Oregon Health & Science University

You can click a keyword to filter the displayed items

health sciences diabetes machine learning diabetes technology diabetes care diabetes management public health biomedical engineering predictive analytics sleep digital health digital medicine blood glucose monitoring type 1 statistics data modeling physical activity statistical models scientific computing biomedical informatics medical image computing computational intelligence diabetes research intelligent computing echocardiography cardiovascular imaging biomedical modeling computational epidemiology physic aware machine learning bioacoustics biomedical data science intermittently connected device ai integration computational medicine diabetes mellitus intelligent diagnostics augmented intelligence ai healthcare clinical decision support systems medical expert systems multiple daily injections nocturnal hypoglycemia ai-powered tool glucose dynamics external evaluation reference standard

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Physiologically-Constrained Neural Network Digital Twin Framework for Replicating Glucose Dynamics in Type 1 Diabetes. Neural Computing and Applications (2026)

diabetes technologybiostatisticsdiabetes carediabetes managementneural computationdiabetes researchblood glucose monitoringsystems biologydiabetesapplied mathematicsglucose dynamicstype 1diabetes mellitus

Evaluation of a Prediction-Based Bedtime Intervention in Reducing Nocturnal Low Glucose in Adults With Type 1 Diabetes: The Dailydose Bedtime Smart Snack Crossover Study. Diabetes Care (2025)

health promotiondiabetes technologyhealth sciencesdiabetes carediabetes managementdiabetessleep

Recent Advancements and Applications of Physics-Informed Machine Learning in Biomedical Research. Current Opinion in Biomedical Engineering (2025)

machine learningscientific computingphysic aware machine learningpredictive analyticsbiomedical engineering

Reply to: Correction to External Evaluation of a Commercial Artificial Intelligence-Augmented Digital Auscultation Platform in Valvular Heart Disease Detection Using Echocardiography as Reference Standard. International Journal of Cardiology (2025)

digital medicinemedical expert systemscardiovascular imagingai healthcaredata scienceaugmented intelligencecardiovascular diseaseemergency medicineclinical decision support systemshealth informaticscardiologydiagnosisexternal evaluationdigital healthreference standardintelligent computingartificial intelligenceintelligent diagnosticsradiologyechocardiography

Combining Uncertainty-Aware Predictive Modeling and a Bedtime Smart Snack Intervention to Prevent Nocturnal Hypoglycemia in People With Type 1 Diabetes on Multiple Daily Injections. Journal of the American Medical Informatics Association (2023)

digital healthdigital medicinediabetes technologyhealth sciencesnocturnal hypoglycemiamultiple daily injectionsdiabetes carediabetes managementchronic diseasespredictive analyticsblood glucose monitoringdiabetespublic healthtype 1sleep

Modeling Risk of Hypoglycemia During and Following Physical Activity in People With Type 1 Diabetes Using Explainable Mixed-Effects Machine Learning. Computers in Biology and Medicine (2023)

Clara Mosquera-LopezKatrina L. RamseyValentina Roquemen-EcheverriPeter G. Jacobs

computational epidemiologystatisticshealth sciencesmachine learningdata modelingdiabetespublic healthstatistical modelsphysical activitybiomedical modeling

An AI-Powered Tool for Automatic Heart Sound Quality Assessment and Segmentation. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021)

Valentina Roquemen-EcheverriPeter G. JacobsStephen HeitnerPeter M. SchulmanBethany WilsonJorge MahechaClara Mosquera-Lopez

ai integrationcomputer sciencehealth informaticscomputational intelligencebioinformaticshealth sciencesinstrumentationmachine learningmedical image computingartificial intelligencebioacousticsai-powered toolintermittently connected devicebiomedical engineeringbiomedical data sciencecomputational medicinebiomedical informatics

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Valentina Roquemen-Echeverri

Oregon Health & Science University

Affiliations

Department Of Artificial Intelligence For Medical Systems

NoneValentina Roquemen-echeverri is currently serving as a Artificial Intelligence For Medical Systems faculty at Oregon Health & Science University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Valentina Roquemen-Echeverri

Oregon Health & Science University

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

A Physiologically-Constrained Neural Network Digital Twin Framework for Replicating Glucose Dynamics in Type 1 Diabetes. Neural Computing and Applications (2026)

Evaluation of a Prediction-Based Bedtime Intervention in Reducing Nocturnal Low Glucose in Adults With Type 1 Diabetes: The Dailydose Bedtime Smart Snack Crossover Study. Diabetes Care (2025)

health promotiondiabetes technologyhealth sciencesdiabetes carediabetes managementdiabetessleep

Recent Advancements and Applications of Physics-Informed Machine Learning in Biomedical Research. Current Opinion in Biomedical Engineering (2025)

machine learningscientific computingphysic aware machine learningpredictive analyticsbiomedical engineering

Modeling Risk of Hypoglycemia During and Following Physical Activity in People With Type 1 Diabetes Using Explainable Mixed-Effects Machine Learning. Computers in Biology and Medicine (2023)

Clara Mosquera-LopezKatrina L. RamseyValentina Roquemen-EcheverriPeter G. Jacobs

computational epidemiologystatisticshealth sciencesmachine learningdata modelingdiabetespublic healthstatistical modelsphysical activitybiomedical modeling

An AI-Powered Tool for Automatic Heart Sound Quality Assessment and Segmentation. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2021)

Valentina Roquemen-EcheverriPeter G. JacobsStephen HeitnerPeter M. SchulmanBethany WilsonJorge MahechaClara Mosquera-Lopez

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