Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach

Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsi...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	JMIR formative research Ročník 9; s. e67969
Hlavní autori:	Subramanian, Ajan, Cao, Rui, Naeini, Emad Kasaeyan, Aqajari, Seyed Amir Hossein, Hughes, Thomas D, Calderon, Michael-David, Zheng, Kai, Dutt, Nikil, Liljeberg, Pasi, Salanterä, Sanna, Nelson, Ariana M, Rahmani, Amir M
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Canada JMIR Publications 27.01.2025
Predmet:	Adult Aged Behavior Chronic pain Data collection Datasets Dementia Electrocardiography Electroencephalography Female Heart rate Humans Machine Learning Male Medical research Middle Aged Minority & ethnic groups Original Paper Pain Measurement - methods Pain, Postoperative - diagnosis Patients Physiology Software United States > US California machine learning approach pain recognition acute pain signal processing pain monitoring pain assessment electrodermal activity pain intensity multimodal machine learning–based framework electromyogram self-reported pain level weak supervision multimodal information fusion machine learning–based framework clinical pain management electrocardiogram pain measurement pain intensity recognition behavioral pain health care
ISSN:	2561-326X, 2561-326X
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!