Hayoung Jeong

Preprint · March 8, 2026 Daylight Saving Time (DST) remains contentious: some policymakers highlight behavioral benefits, while others emphasize health risks. Existing evidence relies largely on aggregated data and strict modeling assumptions, obscuring individual-level patterns a ... Full text Link to item Cite

Defining the Habitome: Phenotypes of Routine and Their Relationship to Health Outcomes

Preprint · 2025 AbstractHuman health is deeply interconnected with behaviors that are dictated by daily routines, including activities such as sleep, physical activity, and dietary habits. Wearable technologies like smartwatches provide continuous, rea ... Full text Cite

Stepping Up for All of Us: Data from the All of Us Research Program Reinforces Existence of Activity Inequality in the United States

Preprint · 2023 AbstractData from digital health technologies can provide insights into a population’s daily activity levels and behaviors. Using Fitbit wearable data from 7,431 participants enrolled in the All of Us Research Program, ... Full text Cite

Considerations while using Fitbit Data in the All of Us Research Program: Tutorial (Preprint)

Preprint · December 16, 2022 UNSTRUCTUREDBackground: Wearable biometric monitoring technologies (BioMeTs) have become increasingly popular in recent years, especially as BioMeTs have been improving, offering more ca ... Full text Cite

A Machine Learning Algorithm to Predict Hypoxic Respiratory Failure and risk of Acute Respiratory Distress Syndrome (ARDS) by Utilizing Features Derived from Electrocardiogram (ECG) and Routinely Clinical Data

Preprint · 2022 Full text Cite

Cluster analysis driven by unsupervised latent feature learning of intensive care unit medications to identify novel pharmaco-phenotypes of critically ill patients

Preprint · 2022 Full text Cite