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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
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Editorial: Non-linear analysis and machine learning in cardiology

Hans Dierckx1,2, Xiaopeng Zhao3, Elena G Tolkacheva4,5,6

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No abstract available in PubMed .

Keywords:
MLcardiology (basic/technical)data analysismachine learningmultiscale modeling and analysisnon-linear analysis methodologies

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