Objective Detection of Newborn Infant Acute Procedural Pain Using EEG and Machine Learning Algorithms.

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Tác giả: Kanwaljeet J S Anand, Amir Avnit, Behnood Gholami, Wassim M Haddad, Jean-Michel Roué

Ngôn ngữ: eng

Ký hiệu phân loại: 006.31 Machine learning

Thông tin xuất bản: United States : Paediatric & neonatal pain , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 687571

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Observer-dependent infant pain scales have limitations including discontinuous assessments and the lack of healthcare professionals' availability. We hypothesized that applying agnostic machine learning approaches to neonatal electroencephalographic (EEG) analysis may reveal features of the infant response to acute pain. EEG was recorded from 30 neonates undergoing acutely painful procedures (18 males, 34.0-41.7 weeks gestation at birth). EEG recordings were randomly assigned to training (

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