Pain Assessment in Neonatal Clinical Practice via Facial Expression Analysis and Deep Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-64636-2_19
Reference47 articles.
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2. Bergamasco, L., Gavelli, M., Fadda, C., Parodi, E., Bondone, C., Castagno, E.: Measurement of acute pain in the pediatric emergency department through automatic detection of behavioral parameters: a pilot study. In: Bioinformatics and Biomedical Engineering, pp. 469–481. Springer Nature Switzerland, Cham (2023). https://doi.org/10.1007/978-3-031-34953-9_37
3. Brahnam, S., Chuang, C.F., Sexton, R.S., Shih, F.Y.: Machine assessment of neonatal facial expressions of acute pain. Decis. Support Syst. 43(4), 1242–1254 (2007). https://doi.org/10.1016/j.dss.2006.02.004, special Issue Clusters
4. Brahnam, S., Chuang, C.F., Shih, F.Y., Slack, M.R.: Machine recognition and representation of neonatal facial displays of acute pain. Artif. Intell. Med. 36(3), 211–222 (2006). https://doi.org/10.1016/j.artmed.2004.12.003
5. Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence);S Brahnam,2006
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