Cardiopulmonary Comorbidity, Radiomics and Machine Learning, and Therapeutic Regimens for a Cerebral fMRI Predictor Study in Psychotic Disorders
Recently, two researches by Doucet et al. and Collin et al. used functional neuroimaging as a tool to improve the management of schizophrenia and other psychotic disorders [1, 2]. We would like to highlight several issues in relation to cardiopulmonary comorbidity, radiomics and machine learning, and therapeutic regimens, along with their clinical implications.
Gaelle E. Doucet and colleagues assessed the predictive potential of baseline brain functional magnetic resonance imaging (fMRI) and structural MRI (before treatment with antipsychotics for 24 weeks) in patients with schizophrenia . Intriguingly, this study indicated the cohesiveness of the default mode and central executive networks and their integration with the salience, somatosensory, and visual networks as key predictors of symptomatic change in early schizophrenia. Gussje Collin and colleagues assessed the predictive potential of the baseline functional connectome based on MRI that precedes conversion to psychosis...
This highlight was supported by grants from the National Natural Science Foundation of China (81801675) and the Military Medical Major Program during the Thirteenth Five-Year Plan Period of China (AWS17J012).
Conflict of interest
We declare that we have no conflict of interest.
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