Academic Journal
Remote monitoring of positive airway pressure data: Challenges, Pitfalls and Strategies to consider for optimal data science applications
| العنوان: | Remote monitoring of positive airway pressure data: Challenges, Pitfalls and Strategies to consider for optimal data science applications |
|---|---|
| المؤلفون: | Bottaz-Bosson, Guillaume, Midelet, Alphanie, Mendelson, Monique, Borel, Jean-Christian, Martinot, Jean-Benoît, Le Hy, Ronan, Schaeffer, Marie-Caroline, Samson, Adeline, Hamon, Agnès, Tamisier, Renaud, Malhotra, Atul, Pépin, Jean-Louis, Bailly, Sébastien |
| المساهمون: | Hypoxie et PhysioPathologie (HP2), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes (UGA), Université de Namur Namur (UNamur), Probayes Montbonnot-Saint-Martin, Université Grenoble Alpes (UGA), University of California San Diego (UC San Diego), University of California (UC), ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019) |
| المصدر: | ISSN: 0012-3692. |
| بيانات النشر: | HAL CCSD American College of Chest Physicians |
| سنة النشر: | 2022 |
| مصطلحات موضوعية: | Data management, Positive Airway Pressure, Remote monitoring, Time series, obstructive sleep apnea, [SDV]Life Sciences [q-bio], envir, geo |
| الوصف: | International audience ; Over recent years positive airway pressure (PAP) remote monitoring has transformed the management of obstructive sleep apnea and produced a large amount of data. Accumulated PAP data provide valuable and objective information regarding patient treatment adherence and efficiency. However, the majority of studies analyzing longitudinal PAP remote monitoring summarize data trajectories in static and simplistic metrics for PAP adherence and the residual apnea-hypopnea index (AHI) by using mean or median values. The aims of this article are to suggest directions for improving data cleaning and processing and to address major concerns for data science applications including: 1) conditions for rAHI reliability, 2) lack of standardization of indicators provided by different PAP models, 3) missing values and 4) consideration of treatment interruptions. To allow fair comparison between studies and to avoid biases in computation, PAP data processing and management should be conducted rigorously with these points in mind. PAP remote monitoring data contain a wealth of information that is currently underused in the field of sleep research. Improving the quality and standardizing data handling could facilitate data sharing among specialists worldwide and enable artificial intelligence strategies to be applied in the field of sleep apnea. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | https://www.hal.inserm.fr/inserm-03941644 |
| الاتاحة: | https://www.hal.inserm.fr/inserm-03941644 |
| Rights: | undefined |
| رقم الانضمام: | edsbas.A964FFDA |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |