Mary S. Kim

TextAidAR: Text-driven domain knowledge for fine-grained medical activity recognition

Wenjin Zhang, Chenyang Gao, Sifan Yuan, Mary S. Kim et autres

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Automatic Detection of Physiological Attributes from Verbal Communication During Time-Critical Medical Events

Chenyang Gao, Wenjin Zhang, Aaron H. Mun, Aleksandra Sarcevic et autres

In this study, we present a proof-of-concept system exploring the feasibility of automatically capturing physiological values during the primary survey phase of trauma resuscitation—a complex, time-sensitive evaluation of severely injured patients. We developed and evaluated a speech-driven activity recognition system designed to …

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Multi-view real-time detection of patient arrival in trauma resuscitation using computer vision

Sifan Yuan, Mary S. Kim, Aaron H. Mun, Rebecca Cunningham et autres

Every minute delay in life-saving intervention increases mortality risk in injured patients. Given this relationship, quality measurement of trauma resuscitation includes the timing of provider decisions and interventions. The current approach of manual recording of patient arrival and other timestamps may be …

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Consensus-based criteria for actionable hemorrhage in pediatric trauma: A Delphi study

Mary S. Kim, Aaron H. Mun, Dylan W. Arkowitz, Tamara Sharf et autres

BACKGROUND: Blood transfusion and hemorrhage control procedures can be unreliable surrogates for bleeding requiring intervention in children. Some receive unnecessary blood transfusions or lack intraoperative findings for hemorrhage, while others die before an intervention occurs. Standardized criteria for adjudicating the presence of …

SAFE: A Smart Adherence Detection Framework for Monitoring Personal Protective Equipment in Healthcare Settings

Wanzhao Yang, Beomseok Park, Mary S. Kim, Aleksandra Sarcevic et autres

Personal protective equipment (PPE) is critical for infection control in healthcare, protecting workers and patients from infection risks. The COVID-19 pandemic further highlighted the importance of correct PPE use, yet adherence to U.S. Centers for Disease Control and Prevention guidelines remains inconsistent. …

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Computer-vision based recognition of cervical spine stabilization during trauma resuscitation

Mary S. Kim, Sifan Yuan, Genevieve J. Sippel, Aaron H. Mun et autres

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To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events

Angela Mastrianni, Mary S. Kim, Travis M. Sullivan, Genevieve J. Sippel et autres

AI-enabled decision-support systems aim to help medical providers rapidly make decisions with limited information during medical emergencies. A critical challenge in developing these systems is supporting providers in interpreting the system output to make optimal treatment decisions. In this study, we designed …

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Timing and type of personal protective equipment adherence lapses in pediatric trauma resuscitation: A retrospective video study

Mary S. Kim, Dylan W. Arkowitz, Aleksandra Sarcevic, Randall S. Burd

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Understanding Personal Protective Equipment Use in Interdisciplinary Medical Settings: Design Explorations for Just-in-Time Compliance Alerts

Aleksandra Sarcevic, Eleanor A. Wood, Katherine Ann Zellner, Christine Dodeye Ikponmwonba et autres

We examine the use of personal protective equipment (PPE) in two interdisciplinary medical settings to inform the design of just-in-time alerts and reminders for correcting PPE noncompliance. We reviewed videos of 26 pediatric resuscitations occurring over the course of the COVID-19 pandemic …

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STop Clock for Automated Tracking (STAT) during Time-Critical Medical Work: Evaluating the Accuracy and Usability of an AI-Driven Automated Stop Clock

Katherine Ann Zellner, Sifan Yuan, Emily R. Ernst, Dylan W. Arkowitz et autres

To Recommend or Not to Recommend: Designing and Evaluating AI-Enabled Decision Support for Time-Critical Medical Events

Angela Mastrianni, Mary S. Kim, Travis M. Sullivan, Genevieve J. Sippel et autres

AI-enabled decision-support systems aim to help medical providers rapidly make decisions with limited information during medical emergencies. A critical challenge in developing these systems is supporting providers in interpreting the system output to make optimal treatment decisions. In this study, we designed …

Development of an algorithm for adjudicating actionable hemorrhage in pediatric trauma patients

Mary S. Kim, Genevieve J. Sippel, Travis M. Sullivan, Nathan J. Alcasid et autres

BACKGROUND: Bleeding is the leading cause of preventable death in trauma. Early identification of hemorrhage improves patient outcomes. Current triage tools for predicting hemorrhage rely on transfusion receipt as a surrogate outcome, indicating that blood was needed. This outcome does not account …

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