Nikhlil Bhagwat
Affiliations: | The Allen Institute for Brain Science |
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| Bhagwat N, Barry A, Dickie EW, et al. (2021) Understanding the impact of preprocessing pipelines on neuroimaging cortical surface analyses. Gigascience. 10 |
| Talpalaru A, Bhagwat N, Devenyi GA, et al. (2019) Identifying schizophrenia subgroups using clustering and supervised learning. Schizophrenia Research |
| Bhagwat N, Pipitone J, Voineskos AN, et al. (2019) An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures Journal of Psychiatry & Neuroscience : Jpn. 44: 1-15 |
| Bhagwat N, Viviano JD, Voineskos AN, et al. (2018) Modeling and prediction of clinical symptom trajectories in Alzheimer's disease using longitudinal data. Plos Computational Biology. 14: e1006376 |
| Winterburn JL, Voineskos AN, Devenyi GA, et al. (2017) Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study. Schizophrenia Research |
| Sankar T, Park MT, Jawa T, et al. (2017) Your algorithm might think the hippocampus grows in Alzheimer's disease: Caveats of longitudinal automated hippocampal volumetry. Human Brain Mapping |
| Makowski C, Béland S, Kostopoulos P, et al. (2017) Evaluating Accuracy of Striatal, Pallidal, and Thalamic Segmentation Methods: Comparing Automated Approaches to Manual Delineation. Neuroimage |
| Bhagwat N, Pipitone J, Winterburn JL, et al. (2016) Manual-Protocol Inspired Technique for Improving Automated MR Image Segmentation during Label Fusion. Frontiers in Neuroscience. 10: 325 |
| Chakravarty M, Amaral RS, Bhagwat N, et al. (2016) F4-04-02: Interpreting Disease Heterogeneity in Alzheimer's and Parkinson's Disease Alzheimer's & Dementia. 12: P327-P328 |
| Bhagwat N, Pipitone J, Park MTM, et al. (2016) P4-210: Neural-Net Model for Predicting Clinical Symptom Scores in Alzheimer's Disease Alzheimer's & Dementia. 12: P1105-P1106 |