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Predictive Modeling in Medicine
Encyclopedia, 2023 Predictive modeling is a complex methodology that involves leveraging advanced mathematical and computational techniques to forecast future occurrences or outcomes.
Milan Toma, Ong Chi Wei
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Predictive Modeling of Weight Loss and Metabolic Health Outcomes: A Retrospective Predictive Modeling Study [PDF]
Health Science ReportsBackground Obesity is a chronic, complicated, and progressive disease that significantly affects mortality, quality of life, and overall health in nearly 13% of the adult population worldwide.
Rolando Andrade‐Calle +2 more
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IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 Background. There is a worldwide health crisis stemming from the rising incidence of various debilitating chronic diseases, with stroke as a leading contributor.
Katryna Cisek, John D. Kelleher
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Spectral EEG correlations from the different phases of general anesthesia
Frontiers in Medicine, 2023 IntroductionElectroencephalography (EEG) signals contain transient oscillation patterns commonly used to classify brain states in responses to action, sleep, coma or anesthesia.MethodsUsing a time-frequency analysis of the EEG, we search for possible ...
Christophe Sun +3 more
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Journal of Modern Power Systems and Clean Energy, 2021 We aim to provide a tool for independent system operators to detect the collusion and identify the colluding firms by using day-ahead data. In this paper, an approach based on supervised machine learning is presented for collusion detection in ...
Peyman Razmi +2 more
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Which Upstream Solar Wind Conditions Matter Most in Predicting Bz Within Coronal Mass Ejections
Space Weather, 2023 Accurately predicting the z‐component of the interplanetary magnetic field, particularly during the passage of an interplanetary coronal mass ejection (ICME), is a crucial objective for space weather predictions.
Pete Riley, M. A. Reiss, C. Möstl
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Reflections on predictive modeling for infectious diseases [PDF]
Frontiers in Public HealthDaren Zhao, Daren Zhao
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Continual Sequence Modeling With Predictive Coding
Frontiers in Neurorobotics, 2022 Recurrent neural networks (RNNs) have been proved very successful at modeling sequential data such as language or motions. However, these successes rely on the use of the backpropagation through time (BPTT) algorithm, batch training, and the hypothesis ...
Louis Annabi +3 more
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Factors that pre-determine the main subtypes of ischemic stroke in middle-aged and senior women [PDF]
Анналы клинической и экспериментальной неврологии, 2023 Introduction. Brain health and active longevity are affected by a number of stroke risk factors. We should identify their relative impact on the main subtypes of ischemic stroke (IS) in middle-aged and senior women to consider prevention and management ...
Marina Yu. Maximova +1 more
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Nature Communications, 2019 Chromatin is folded into Topologically Associating domains (TADs), with the organization and folding hierarchy of the TADs being highly dynamic. Here the authors develop a parsimonious randomly cross-linked (RCL) polymer model that maps high frequency ...
O. Shukron +3 more
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