Antipsychotic-based machine learning models may help prediction of tardive dyskinesia in patients with schizophrenia

Antipsychotic medications are commonly used in the treatment of schizophrenia, but they can sometimes lead to side effects such as tardive dyskinesia, a condition characterized by involuntary movements, particularly of the face and tongue. To address this concern, the integration of machine learning models with antipsychotic treatments shows promise in predicting the likelihood of tardive dyskinesia development in patients with schizophrenia.

By leveraging machine learning algorithms, these models can analyze various factors such as patient demographics, medication history, genetic markers, and other relevant data to generate predictive insights. This approach offers a more personalized and proactive method for identifying individuals who may be at a higher risk of developing tardive dyskinesia.

to cite the paper:

Uludag K, Wang DM, Mohamoud Y, Wu HE, Zhang X. Antipsychotic-based machine learning models may help prediction of tardive dyskinesia in patients with schizophrenia. Schizophr Res. 2023 Feb;252:33-35. doi: 10.1016/j.schres.2022.12.026. Epub 2023 Jan 6. PMID: 36621324.
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