Výsledky vyhledávání - "Nor Safira Elaina Mohd Noor"

Akademický článek

Improving Outcome Prediction for Traumatic Brain Injury From Imbalanced Datasets Using RUSBoosted Trees on Electroencephalography Spectral Power

Autor: Nor Safira Elaina Mohd Noor, Haidi Ibrahim, Muhammad Hanif Che Lah, Jafri Malin Abdullah

Publikováno v: IEEE Access, Vol 9, Pp 121608-121631 (2021)

Reliable prediction of traumatic brain injury (TBI) outcomes based on machine learning (ML) that is derived from quantitative electroencephalography (EEG) features has renewed interest in recent years. Nevertheless, the approach has suffered from imb

Externí odkaz: https://doaj.org/article/5c60d9455ad14af69f61de1d9c41af8d

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Akademický článek

Machine Learning Algorithms and Quantitative Electroencephalography Predictors for Outcome Prediction in Traumatic Brain Injury: A Systematic Review

Autor: Nor Safira Elaina Mohd Noor, Haidi Ibrahim

Publikováno v: IEEE Access, Vol 8, Pp 102075-102092 (2020)

Recent developments in the field of machine learning (ML) have led to a renewed interest in the use of electroencephalography (EEG) to predict the outcome after traumatic brain injury (TBI). This systematic review aims to determine how previous studi

Externí odkaz: https://doaj.org/article/a3a297616e8748ecb6ca579b3f5e6856

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Akademický článek

A Long Short-Term Memory Network Using Resting-State Electroencephalogram to Predict Outcomes Following Moderate Traumatic Brain Injury

Autor: Nor Safira Elaina Mohd Noor, Haidi Ibrahim, Chi Qin Lai, Jafri Malin Abdullah

Publikováno v: Computers, Vol 12, Iss 2, p 45 (2023)

Although traumatic brain injury (TBI) is a global public health issue, not all injuries necessitate additional hospitalisation. Thinking, memory, attention, personality, and movement can all be negatively impacted by TBI. However, only a small propor

Externí odkaz: https://doaj.org/article/f0cbad2b2d304dfeb4a1d5bf309ed997

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Machine Learning Algorithms and Quantitative Electroencephalography Predictors for Outcome Prediction in Traumatic Brain Injury: A Systematic Review

Autor: Haidi Ibrahim, Nor Safira Elaina Mohd Noor

Publikováno v: IEEE Access, Vol 8, Pp 102075-102092 (2020)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1298a681444276728077c92f74f0ac28
https://doi.org/10.1109/access.2020.2998934

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Prediction of Recovery from Traumatic Brain Injury with EEG Power Spectrum in Combination of Independent Component Analysis and RUSBoost Model

Autor: Nor Safira Elaina Mohd Noor, Haidi Ibrahim, Muhammad Hanif Che Lah, Jafri Malin Abdullah

Publikováno v: BioMedInformatics; Volume 2; Issue 1; Pages: 106-123

The computational electroencephalogram (EEG) is recently garnering significant attention in examining whether the quantitative EEG (qEEG) features can be used as new predictors for the prediction of recovery in moderate traumatic brain injury (TBI).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d97ea04eba40af251b73c10d5400d84

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Predicting Outcomes in Patients with Traumatic Brain Injury Using Machine Learning Models

Autor: Haidi Ibrahim, Nor Safira Elaina Mohd Noor

Publikováno v: Lecture Notes in Mechanical Engineering ISBN: 9789811395383

Traumatic brain injury (TBI) is defined as blunt and penetrating injury to the head and/or brain caused by an external force that leads to temporary or permanent impairments to the brain function. Accurate measurement of prediction for the outcomes o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::86291613cf61802778919afaf0da2e85
https://doi.org/10.1007/978-981-13-9539-0_2