Ran Xiao

Assistant Professor

Emory University

United States

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Ran Xiao is an Assistant Professor at Emory University in the United States. His research primarily focuses on precision critical care, particularly through the integration of machine learning and multimodal physiological data. Recent publications highlight his work on photoplethysmography for atrial fibrillation detection, EEG measures related to cognitive development, and the impact of label noise on learning models in clinical settings.

Articles (13)

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2025

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2024

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2024

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2022

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2021

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2020

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2020

Collaborators (3)

Beth A. Smith

Associate Professor

University of Southern California / Children's Hospital Los Angeles

UNITED STATES

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Cynthia Rudin

Duke University

UNITED STATES

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Duc Do

University of California, Los Angeles

UNITED STATES

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Ran Xiao

Research Interests

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Articles (13)

Treatment response phenotyping informed by patient physiology could drive precision critical care through augmented intelligence. A Narrative Review

Associations between EEG power and coherence with cognition and early precursors of speech and language development across the first months of life

Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms

Photoplethysmography based atrial fibrillation detection: a continually growing field

Integrating multimodal information in machine learning for classifying acute myocardial infarction

Log-Spectral Matching GAN: PPG-Based Atrial Fibrillation Detection can be Enhanced by GAN-Based Data Augmentation With Integration of Spectral Loss

Impact of Label Noise on the Learning Based Models for a Binary Classification of Physiological Signal

Time Synchronization of Multimodal Physiological Signals through Alignment of Common Signal Types and Its Technical Considerations in Digital Health

Technical considerations for evaluating clinical prediction indices: a case study for predicting code blue events with MEWS

Electroencephalography measures of relative power and coherence as reaching skill emerges in infants born preterm

Explainability Metrics of Deep Convolutional Networks for Photoplethysmography Quality Assessment

A Supervised Approach to Robust Photoplethysmography Quality Assessment

Generalizability of SuperAlarm via Cross-Institutional Performance Evaluation

Collaborators (3)

Beth A. Smith

Cynthia Rudin

Duc Do

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