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Filtres: Auteur is Bhagwat, Nikhil [Enlever les filtres]
Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study. Schizophr Res.. 2017.
Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.. Gen Hosp Psychiatry. 47:20-28.. 2017.
Evaluating accuracy of striatal, pallidal, and thalamic segmentation methods: Comparing automated approaches to manual delineation.. Neuroimage. 170:182-198.. 2018.
Identifying schizophrenia subgroups using clustering and supervised learning.. Schizophr Res. 214:51-59.. 2019.
Manual-Protocol Inspired Technique for Improving Automated MR Image Segmentation during Label Fusion.. Front Neurosci. 10:325.. 2016.
Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses.. Gigascience. 10(1). 2021.
Your algorithm might think the hippocampus grows in Alzheimer's disease: Caveats of longitudinal automated hippocampal volumetry.. Hum Brain Mapp. 38(6):2875-2896.. 2017.