AIMC Topic: Antipsychotic Agents
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Predicting maintenance lithium response for bipolar disorder from electronic health records-a retrospective study.
PeerJ
Oct 14, 2024
BACKGROUND: Optimising maintenance drug treatment selection for people with bipolar disorder is challenging. There is some evidence that clinical and demographic features may predict response to lithium. However, attempts to personalise treatment cho...
Predicting remission after acute phase pharmacotherapy in patients with bipolar I depression: A machine learning approach with cross-trial and cross-drug replication.
Bipolar disorders
Oct 3, 2024
OBJECTIVES: Interpatient variability in bipolar I depression (BP-D) symptoms challenges the ability to predict pharmacotherapeutic outcomes. A machine learning workflow was developed to predict remission after 8 weeks of pharmacotherapy (total score ...
Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.
BMC medical informatics and decision making
Aug 2, 2024
PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for antipsychotic drug (risperidone) continuation in children and teenagers suffering from mania over one year and to discover potential variables for cl...
Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features.
Schizophrenia research
May 31, 2024
Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be beneficial for implementing individually adapted therapeutic strategies and better understanding the TRS etiology. The aim of this study was to explore, wi...
Illusory generalizability of clinical prediction models.
Science (New York, N.Y.)
Jan 11, 2024
It is widely hoped that statistical models can improve decision-making related to medical treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically based on investigators observing a model's success in one or two d...
Effectiveness and safety of blonanserin for improving social and cognitive functions in patients with first-episode schizophrenia: a study protocol for a prospective, multicentre, single-arm clinical trial.
BMJ open
Apr 20, 2022
INTRODUCTION: Both the pharmacological characteristics of blonanserin and its related small sample size studies suggest that blonanserin could alleviate social and cognitive dysfunctions in patients with schizophrenia. However, no large sample size s...
Proteome-Informed Machine Learning Studies of Cocaine Addiction.
The journal of physical chemistry letters
Nov 9, 2021
No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate molecular mechanisms of cocaine addiction, involving synergistic interactions among proteins upstrea...
Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials.
Clinical and translational science
May 3, 2021
Clinical trial efficiency, defined as facilitating patient enrollment, and reducing the time to reach safety and efficacy decision points, is a critical driving factor for making improvements in therapeutic development. The present work evaluated a m...
Pattern classification as decision support tool in antipsychotic treatment algorithms.
Experimental neurology
Feb 4, 2021
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic...
Predicting self-harm within six months after initial presentation to youth mental health services: A machine learning study.
PloS one
Dec 31, 2020
BACKGROUND: A priority for health services is to reduce self-harm in young people. Predicting self-harm is challenging due to their rarity and complexity, however this does not preclude the utility of prediction models to improve decision-making rega...
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