The butterfly effect in oral and maxillofacial surgery: Understanding and applying chaos theory and complex systems principles
R Grillo, BAQ Reis, BC Lima, LAPF Pinto… - Journal of Cranio …, 2024 - Elsevier
Purpose The present paper provides a historical context for chaos theory, originating in the
1960s with Edward Norton Lorenz's efforts to predict weather patterns. It introduces chaos …
1960s with Edward Norton Lorenz's efforts to predict weather patterns. It introduces chaos …
Deep learning forecasts the occurrence of sleep apnea from single-lead ECG
M Bahrami, M Forouzanfar - Cardiovascular Engineering and Technology, 2022 - Springer
Objectives Sleep apnea is the most common sleep disorder that leads to serious health
complications if not treated early. Forecasting apnea occurrence ahead in time provides the …
complications if not treated early. Forecasting apnea occurrence ahead in time provides the …
Time series forecasting for healthcare diagnosis and prognostics with the focus on cardiovascular diseases
Time series forecasting has been a prosperous filed of science due to its popularity in real-
world applications, yet being challenge in method developments. In medical applications …
world applications, yet being challenge in method developments. In medical applications …
Probabilistic domain-knowledge modeling of disorder pathogenesis for dynamics forecasting of acute onset
Disease pathogenesis, a type of domain knowledge about biological mechanisms leading to
diseases, has not been adequately encoded in machine-learning-based medical diagnostic …
diseases, has not been adequately encoded in machine-learning-based medical diagnostic …
A noise-robust Koopman spectral analysis of an intermittent dynamics method for complex systems: A case study in pathophysiological processes of obstructive sleep …
Koopman operator theory and the Hankel alternative view of the Koopman (HAVOK) model
have been widely used to investigate the chaotic dynamics in complex systems. Although …
have been widely used to investigate the chaotic dynamics in complex systems. Although …
Deep Learning and Recurrence Information Analysis for the Automatic Detection of Obstructive Sleep Apnea
Obstructive sleep apnea (OSA) represents a significant health concern. While
polysomnography (PSG) remains the gold standard, its resource-intensive nature has …
polysomnography (PSG) remains the gold standard, its resource-intensive nature has …
A quantization of deep belief networks for long short-term memory in sleep stage detection
The study proposes the use of Deep Belief Networks (DBN) as quantization for inputs from
Long Short-Term Memory (LSTM), called qLSTM. The system was tested using the sleep …
Long Short-Term Memory (LSTM), called qLSTM. The system was tested using the sleep …
A recurrent gated unit-based mixture kriging machine Bayesian filtering approach for long-term prediction of dynamic intermittency
The performance of long-term prediction models is currently impeded due to the mismatch
between the nonstationary representations of statistical learning models and the underlying …
between the nonstationary representations of statistical learning models and the underlying …
Detecting changes in transient complex systems via dynamic network inference
HM Tran, STS Bukkapatnam, M Garg - IISE Transactions, 2019 - Taylor & Francis
Graph analytics methods have evoked significant interest in recent years. Their applicability
to real-world complex systems is currently limited by the challenges of inferring effective …
to real-world complex systems is currently limited by the challenges of inferring effective …
Causal Inference in Longitudinal Studies Using Causal Bayesian Network with Latent Variables
Longitudinal studies have been broadly used in clinical research to investigate the
associations between exposures or treatments and the outcome of the diseases, such as …
associations between exposures or treatments and the outcome of the diseases, such as …