Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1
Y Pan, X Zhang, X Wen, N Yuan, L Guo, Y Shi, Y Jia… - Sleep Medicine, 2024 - Elsevier
Background Major depression disorder (MDD) forms a common psychiatric comorbidity
among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often …
among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often …
Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness
Y Pan, D Zhao, X Zhang, N Yuan, L Yang… - Nature and Science …, 2024 - Taylor & Francis
Background Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive
sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be …
sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be …
0574 Artificial Intelligence to Aid in Diagnosis of Type I Narcolepsy
Abstract Introduction Accurate diagnosis of Type 1 narcolepsy (T1N) is cumbersome–
involving clinical, biological, and electrophysiological components. Multiple sleep latency …
involving clinical, biological, and electrophysiological components. Multiple sleep latency …
The application of machine learning on brain imaging features of different narcolepsy subtypes
WC Chin, SY Huang, FY Liu, CH Wang, I Tang… - Sleep, 2024 - academic.oup.com
Abstract Study Objectives Narcolepsy is a central hypersomnia disorder, and differential
diagnoses between its subtypes can be difficult. Hence, we applied machine learning to …
diagnoses between its subtypes can be difficult. Hence, we applied machine learning to …
Major depressive disorder prediction based on sleep-wake disorders symptoms in US adolescents: a machine learning approach from national sleep research …
J Luo, Y Chen, Y Tao, Y Xu, K Yu, R Liu… - Psychology research …, 2024 - Taylor & Francis
Background There is substantial evidence from previous studies that abnormalities in sleep
parameters associated with depression are demonstrated in almost all stages of sleep …
parameters associated with depression are demonstrated in almost all stages of sleep …
Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning
Z Zhang, G Mayer, Y Dauvilliers, G Plazzi, F Pizza… - Scientific reports, 2018 - nature.com
Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or
type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies …
type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies …
Potential of Machine Learning for Predicting Sleep Disorders: A Comprehensive Analysis of Regression and Classification Models
Sleep disorder is a disease that can be categorized as both an emotional and physical
problem. It imposes several difficulties and problems, such as distress during the day, sleep …
problem. It imposes several difficulties and problems, such as distress during the day, sleep …
Narcolepsy Severity Scale-2 and Idiopathic Hypersomnia Severity Scale to better quantify symptoms severity and consequences in Narcolepsy type 2
L Barateau, S Chenini, C Denis, Q Lorber, S Béziat… - Sleep, 2024 - academic.oup.com
Abstract Study Objectives Narcolepsy type 2 (NT2) is an understudied central disorder of
hypersomnolence sharing some similarities with narcolepsy type 1 and idiopathic …
hypersomnolence sharing some similarities with narcolepsy type 1 and idiopathic …
0662 Accurate Automated Sleep Staging of Narcoleptic Patients Using a Machine Learning Model
A Cakir, D Josephs, D Kleinschmidt, J Pathmanathan… - Sleep, 2024 - academic.oup.com
Introduction Accurate sleep staging of EEG data from polysomnography (PSG) is important
in the diagnosis of narcolepsy. Human sleep staging is costly and labor intensive, but …
in the diagnosis of narcolepsy. Human sleep staging is costly and labor intensive, but …
Use of machine learning to identify risk factors for insomnia
AA Huang, SY Huang - PloS one, 2023 - journals.plos.org
Importance Sleep is critical to a person's physical and mental health, but there are few
studies systematically assessing risk factors for sleep disorders. Objective The objective of …
studies systematically assessing risk factors for sleep disorders. Objective The objective of …
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