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Preprint (Author's original)arXiv.org - Non-exclusive license to distribute, Open
Preprint
Interpretable Models for Detecting and Monitoring Elevated Intracranial Pressure
arXiv.org
04 Mar 2024
Abstract
Detecting elevated intracranial pressure (ICP) is crucial in diagnosing and managing various neurological conditions. These fluctuations in pressure are transmitted to the optic nerve sheath (ONS), resulting in changes to its diameter, which can then be detected using ultrasound imaging devices. However, interpreting sonographic images of the ONS can be challenging. In this work, we
propose two systems that actively monitor the ONS diameter throughout an ultrasound video and make a final prediction as to whether ICP is elevated. To construct our systems, we leverage subject matter expert (SME) guidance, structuring our processing pipeline according to their collection procedure, while also prioritizing interpretability and computational efficiency. We conduct a number of experiments, demonstrating that our proposed systems are able to outperform various baselines. One of our SMEs then manually validates our top system's performance, lending further credibility to our approach while demonstrating its potential utility in a clinical setting.
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Details
- Title
- Interpretable Models for Detecting and Monitoring Elevated Intracranial Pressure
- Creators
- Darryl Hannan - Drexel UniversitySteven C Nesbit - Drexel UniversityXiming Wen - Drexel UniversityGlen Smith - Drexel UniversityQiao Zhang - Drexel UniversityAlberto Goffi - University of TorontoVincent Chan - University of TorontoMichael J Morris - Brooke Army Medical CenterJohn C Hunninghake - Brooke Army Medical CenterNicholas E Villalobos - Brooke Army Medical CenterEdward Kim - Drexel UniversityRosina O Weber - Drexel UniversityChristopher J MacLellan - Georgia Institute of Technology
- Publication Details
- arXiv.org
- Resource Type
- Preprint
- Language
- English
- Academic Unit
- Information Science (Informatics); Computer Science (Computing); College of Computing and Informatics
- Other Identifier
- 991021861568004721