Venlafaxine Hydrochloride

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Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

JAMA network open 32568399

IMPORTANCE: Despite the high prevalence and potential outcomes of major depressive disorder, whether and how patients will respond to antidepressant medications is not easily predicted.

Adult Algorithms Antidepressive Agents Citalopram Clinical Decision Rules Depressive Disorder, Major Electroencephalography Female Humans Machine Learning Male Middle Aged Prognosis Prospective Studies Sertraline Treatment Outcome Venlafaxine Hydrochloride

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Developing a machine learning model for predicting venlafaxine active moiety concentration: a retrospective study using real-world evidence.

International journal of clinical pharmacy 38753076

BACKGROUND: Venlafaxine is frequently prescribed for patients with depression. To control the concentration of venlafaxine within the therapeutic window for the best treatment effect, a model to predict venlafaxine concentration is necessary.

Adult Aged Antidepressive Agents, Second-Generation Depression Female Humans Machine Learning Male Middle Aged Retrospective Studies Venlafaxine Hydrochloride

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Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data.

International journal of clinical pharmacy 38733475

BACKGROUND: Venlafaxine dose regimens vary considerably between individuals, requiring personalized dosing.

Adult Aged Antidepressive Agents, Second-Generation Artificial Intelligence Depression Dose-Response Relationship, Drug Female Humans Male Middle Aged Precision Medicine Retrospective Studies Venlafaxine Hydrochloride

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Venlafaxine Hydrochloride

Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

Developing a machine learning model for predicting venlafaxine active moiety concentration: a retrospective study using real-world evidence.

Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data.

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