AIMC Topic: Sleep
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Predicting daily recovery during long-term endurance training using machine learning analysis.
European journal of applied physiology
Jun 20, 2024
PURPOSE: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, s...
Using explainable machine learning and fitbit data to investigate predictors of adolescent obesity.
Scientific reports
May 31, 2024
Sociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wear...
Quantifying Nocturnal Scratch in Atopic Dermatitis: A Machine Learning Approach Using Digital Wrist Actigraphy.
Sensors (Basel, Switzerland)
May 24, 2024
Nocturnal scratching substantially impairs the quality of life in individuals with skin conditions such as atopic dermatitis (AD). Current clinical measurements of scratch rely on patient-reported outcomes (PROs) on itch over the last 24 h. Such meas...
A machine learning model to predict the risk of perinatal depression: Psychosocial and sleep-related factors in the Life-ON study cohort.
Psychiatry research
May 23, 2024
Perinatal depression (PND) is a common complication of pregnancy associated with serious health consequences for both mothers and their babies. Identifying risk factors for PND is key to early detect women at increased risk of developing this conditi...
The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.
Scientific reports
May 13, 2024
Epilepsy surgery is effective for patients with medication-resistant seizures, however 20-40% of them are not seizure free after surgery. Aim of this study is to evaluate the role of linear and non-linear EEG features to predict post-surgical outcome...
Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 9, 2024
To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monitoring typically requires more than 7 hours, which can be inefficient in termxs of data size and analysis. Therefore, we proposed to develop a deep lea...
Identification of sleep phenotypes in COPD using machine learning-based cluster analysis.
Respiratory medicine
May 6, 2024
BACKGROUND: Disturbed sleep in patients with COPD impact quality of life and predict adverse outcomes.
Dysfunctional Beliefs and Attitudes about Sleep-6 (DBAS-6): Data-driven shortened version from a machine learning approach.
Sleep medicine
Apr 27, 2024
BACKGROUND: The Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16) is a widely used self-report instrument for identifying sleep-related cognition. However, its length can be cumbersome in clinical practice. This study aims to develop a ...
Identifying time-resolved features of nocturnal sleep characteristics of narcolepsy using machine learning.
Journal of sleep research
Apr 26, 2024
The differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolence, is challenging due to overlapping symptoms with other hypersomnolence disorders. While recent years have seen significant growth in our understandi...
Elucidating the influence of familial interactions on geriatric depression: A comprehensive nationwide multi-center investigation leveraging machine learning.
Acta psychologica
Apr 17, 2024
OBJECTIVE: A plethora of studies have unequivocally established the profound significance of harmonious familial relationships on the psychological well-being of the elderly. In this study, we elucidate the intergenerational relationships, probing th...
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