Advancing acute respiratory failure management through artificial intelligence: a call for thematic collection contributions
Author:
Funder
Major Research Plan
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1186/s40635-024-00629-4.pdf
Reference6 articles.
1. Messeri L, Crockett MJ (2024) Artificial intelligence and illusions of understanding in scientific research. Nature 627:49–58. https://doi.org/10.1038/s41586-024-07146-0
2. Bouchareb Y, Moradi Khaniabadi P, Al Kindi F et al (2021) Artificial intelligence-driven assessment of radiological images for COVID-19. Comput Biol Med 136:104665. https://doi.org/10.1016/j.compbiomed.2021.104665
3. Suri JS, Agarwal S, Gupta SK et al (2021) A narrative review on characterization of acute respiratory distress syndrome in COVID-19-infected lungs using artificial intelligence. Comput Biol Med 130:104210. https://doi.org/10.1016/j.compbiomed.2021.104210
4. Hong Y, Chen L, Pan Q et al (2021) Individualized Mechanical power-based ventilation strategy for acute respiratory failure formalized by finite mixture modeling and dynamic treatment regimen. EClinicalMedicine 36:100898. https://doi.org/10.1016/j.eclinm.2021.100898
5. Vliegenthart R, Fouras A, Jacobs C, Papanikolaou N (2022) Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry. Respirology 27:818–833. https://doi.org/10.1111/resp.14344
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