A5102859377- Pulmonary Hypertension Research and Treatments
- T-cell and B-cell Immunology
- Renal Transplantation Outcomes and Treatments
- Cardiovascular Function and Risk Factors
- Organ Transplantation Techniques and Outcomes
- Mental Health via Writing
- vaccines and immunoinformatics approaches
- Transplantation: Methods and Outcomes
- Cardiovascular Issues in Pregnancy
- Respiratory viral infections research
- Immune Cell Function and Interaction
- Digital Mental Health Interventions
- Chemokine receptors and signaling
- Monoclonal and Polyclonal Antibodies Research
- Metabolomics and Mass Spectrometry Studies
- Single-cell and spatial transcriptomics
- Cardiac electrophysiology and arrhythmias
- Immunotherapy and Immune Responses
- Cardiac pacing and defibrillation studies
- Mobile Health and mHealth Applications
- Cardiac Valve Diseases and Treatments
- Mass Spectrometry Techniques and Applications
Emory University
2011-2025
Vanderbilt University
2011
Vanderbilt-Ingram Cancer Center
2011
University of Pittsburgh Medical Center
2003-2008
University of Pittsburgh
2003-2007
Recommender systems have great potential in mental health care to personalize self-guided content for patients, allowing them supplement their treatment a scalable way.In this paper, we describe and evaluate 2 knowledge-based recommendation as parts of Ginger, an on-demand platform, bolster engagement content.We developed two algorithms provide recommendations the Ginger smartphone app: (1) one that uses users' responses app onboarding questions recommend cards (2) semantic similarity...
Abstract Summary:Wave-spec is a pre-processing package for mass spectrometry (MS) data. The includes several novel algorithms that overcome conventional difficulties with the of such In this application note, we demonstrate step-by-step use on real-world MALDI dataset. Availability: can be downloaded at http://www.vicc.org/biostatistics/supp.php. A shared mailbox (wave-spec@vanderbilt.edu) also available questions regarding package. Contact: yu.shyr@vanderbilt.edu Supplementary information:...
<sec> <title>BACKGROUND</title> Recommender systems have great potential in mental health care to provide self-guided content supplement the journey for patients scalably; however, traditional filtering approaches often skewed input data distributions, are static or may not account changes symptoms and clinical presentation. In this study, we describe evaluate two knowledge-based recommendation system models as part of Ginger, an on-demand platform that seek address issues above. </sec>...