A5077929387- Chronic Obstructive Pulmonary Disease (COPD) Research
- Machine Learning in Healthcare
- Congenital Diaphragmatic Hernia Studies
- Emergency and Acute Care Studies
- Asthma and respiratory diseases
- Phonocardiography and Auscultation Techniques
- Respiratory Support and Mechanisms
- Explainable Artificial Intelligence (XAI)
- Artificial Intelligence in Healthcare
- Infant Development and Preterm Care
- Childhood Cancer Survivors' Quality of Life
- Machine Learning and Data Classification
- Trauma and Emergency Care Studies
- Pneumonia and Respiratory Infections
- Smoking Behavior and Cessation
- Healthcare Systems and Technology
- Forecasting Techniques and Applications
- Electronic Health Records Systems
- Mobile Health and mHealth Applications
- Adolescent and Pediatric Healthcare
- Pleural and Pulmonary Diseases
- Neonatal Respiratory Health Research
- Statistical and Computational Modeling
- Respiratory viral infections research
- Abdominal Trauma and Injuries
University of Colorado Denver
2018-2025
Children's Hospital Colorado
2018-2022
University of Colorado Anschutz Medical Campus
2021
Pulmonary Associates
2017
Objective: NICU graduates are frequently technology dependent including home oxygen, pulse oximetry, and/or nasogastric (NG) feedings. Primary care provider (PCP) perceptions, practices, and barriers to managing these infants not well described, especially at altitude. We sought 1) describe PCP comfort 2) determine practices in this higher Study design: This cross-sectional survey assessed Colorado Wyoming perceptions surrounding graduates. explored bivariate analysis between clinic...
Asthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations emergency department visits every year. To lower number such encounters, health care systems plans deploy predictive models prospectively identify patients at high risk offer them management services for preventive care. However, previous do not have sufficient accuracy serving this purpose well. Embracing modeling strategy examining candidate features, we built new...
Manual clinical scoring systems are the current standard used for acute asthma care pathways. No automated system exists that assesses disease severity, time course, and treatment impact in pediatric severe exacerbations.machine learning applied to continuous vital sign data could provide a novel pediatric-automated respiratory score (pARS) by using manual (PAS) as standard.Continuous monitoring (heart rate, pulse oximetry) were merged with health record including provider-determined PAS...
Asthma puts a tremendous overhead on healthcare. To enable effective preventive care to improve outcomes in managing asthma, we recently created two machine learning models, one using University of Washington Medicine data and the other Intermountain Healthcare data, predict asthma hospital visits next 12 months patients. As is common learning, neither model supplies explanations for its predictions. tackle this interpretability issue black-box developed an automated method produce...
Sharing data across institutions is critical to improving care for children who are using long-term mechanical ventilation (LTMV). Mechanical complex and poorly standardized. This lack of standardization a major barrier sharing.We aimed describe current ventilator in the electronic health record (EHR) propose framework standardizing these common model (CDM) multiple populations sites.We focused on cohort patients with LTMV dependence were weaned from (MV). We extracted described relevant EHR...
<sec> <title>BACKGROUND</title> Asthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations emergency department visits every year. To lower number such encounters, health care systems plans deploy predictive models prospectively identify patients at high risk offer them management services for preventive care. However, previous do not have sufficient accuracy serving this purpose well. Embracing modeling strategy examining...