Area of research
Radiology, Nuclear Medicine and Imaging · Cognitive Neuroscience
Research interest
Research interests include Functional Brain Connectivity Studies, Dementia and Cognitive Impairment Research, Advanced Neuroimaging Techniques and Applications, and Medical Image Segmentation Techniques.
White Matter Abnormalities and Cognition in Aging and Alzheimer Disease
Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma
The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic drivers
Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Proteomic signatures of corona and herpes viral antibodies identify IGDCC4 as a mediator of neurodegeneration
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
Sleep chart of biological aging clocks in middle and late life
Brain aging patterns in a large and diverse cohort of 49,482 individuals
Proteomics identifies potential immunological drivers of postinfection brain atrophy and cognitive decline
Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice
Genetic and Clinical Correlates of AI-Based Brain Aging Patterns in Cognitively Unimpaired Individuals
Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer’s disease continuum
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements
Proteomic analyses reveal plasma EFEMP1 and CXCL12 as biomarkers and determinants of neurodegeneration
Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer’s disease neuropathology
Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study
Automated tumor segmentation and brain tissue extraction from multiparametric MRI of pediatric brain tumors: A multi-institutional study
Genomic loci influence patterns of structural covariance in the human brain
Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium
Deep learning based detection of enlarged perivascular spaces on brain MRI
Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population
Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium
Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis
Author Correction: Federated learning enables big data for rare cancer boundary detection
Federated learning enables big data for rare cancer boundary detection
The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics
Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation – Analysis of Ranking Scores and Benchmarking Results