AIMC Topic: Circadian Rhythm
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Mining key circadian biomarkers for major depressive disorder by integrating bioinformatics and machine learning.
Aging
Jun 13, 2024
OBJECTIVE: This study aimed to identify key clock genes closely associated with major depressive disorder (MDD) using bioinformatics and machine learning approaches.
Prediction of heart failure patients with distinct left ventricular ejection fraction levels using circadian ECG features and machine learning.
PloS one
May 13, 2024
Heart failure (HF) encompasses a diverse clinical spectrum, including instances of transient HF or HF with recovered ejection fraction, alongside persistent cases. This dynamic condition exhibits a growing prevalence and entails substantial healthcar...
System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.
Cell research
Apr 11, 2024
The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the ...
A three-gene random forest model for diagnosing idiopathic pulmonary fibrosis based on circadian rhythm-related genes in lung tissue.
Expert review of respiratory medicine
Jan 31, 2024
BACKGROUND: The disorder of circadian rhythm could be a key factor mediating fibrotic lung disease Therefore, our study aims to determine the diagnostic value of circadian rhythm-related genes (CRRGs) in IPF.
Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.
Sensors (Basel, Switzerland)
Oct 18, 2023
Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Counseling is the most effective during hospital visits, and the side effects of drugs can be burdensome. Patient empowerment is crucial for understandin...
Automated Secchi disk depth measurement based on artificial intelligence object recognition.
Marine pollution bulletin
Nov 23, 2022
Water transparency affects the degree of sunlight penetration in water, which is important to many water quality processes. It can be visually measured by lowering a Secchi disk (SD) into water and recording its disappearance depth - the Secchi disk ...
Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.
Journal of translational medicine
Apr 28, 2022
BACKGROUND: The circadian system is responsible for regulating various physiological activities and behaviors and has been gaining recognition. The circadian rhythm is adjusted in a 24-h cycle and has transcriptional-translational feedback loops. Whe...
A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.
Journal of pineal research
Jun 20, 2021
The time of dim light melatonin onset (DLMO) is the gold standard for circadian phase assessment in humans, but collection of samples for DLMO is time and resource-intensive. Numerous studies have attempted to estimate circadian phase from actigraphy...
Activation patterns of interictal epileptiform discharges in relation to sleep and seizures: An artificial intelligence driven data analysis.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
May 8, 2021
OBJECTIVE: To quantify effects of sleep and seizures on the rate of interictal epileptiform discharges (IED) and to classify patients with epilepsy based on IED activation patterns.
Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions.
Scientific reports
Jul 29, 2019
A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals on a fixed sleep schedule. This study aimed to test the generalizability of the model to other slee...
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