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Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using a support vector machine classifier

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Bipolar disorder (BD) is a mood disorder with a high morbidity and death rate. Lithium (Li), a prominent mood stabilizer, is often used as a first‐line treatment. However, clinical studies… Click to show full abstract

Bipolar disorder (BD) is a mood disorder with a high morbidity and death rate. Lithium (Li), a prominent mood stabilizer, is often used as a first‐line treatment. However, clinical studies have shown that Li is fully effective in roughly 30% of BD patients. Our goal in this study was to use features derived from information theory to improve the prediction of the patient's response to Li as well as develop a diagnostic algorithm for the disorder.

Keywords: information theory; improve prediction; lithium; bipolar disorder; disorder

Journal Title: Bipolar Disorders
Year Published: 2022

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