An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. - Rahul Desikan; Florent Ségonne; Bruce Fischl; Brian T. Quinn; Bradford C. Dickerson; Deborah Blacker; Randy L. Buckner; Anders M. Dale; Ralph Paul Maguire; Bradley T. Hyman; Marilyn S. Albert; Ronald J. Killiany (NeuroImage, 2006)

Feasibility of Multi-site Clinical Structural Neuroimaging Studies of Aging Using Legacy Data. - Christine Fennema-Notestine; Anthony Collins Gamst; Brian T. Quinn; Jenni Pacheco; Terry L. Jernigan; Leon Thal; Randy L. Buckner; Ron Killiany; Deborah Blacker; Anders M. Dale; Bruce Fischl; Bradford C. Dickerson; et al. (Neuroinformatics, 2007)

Detection of cortical thickness correlates of cognitive performance: Reliability across MRI scan sessions, scanners, and field strengths. - Bradford C. Dickerson; E. Fenstermacher; David H. Salat; David A. Wolk; Ralph Paul Maguire; Rahul Desikan; Jennifer L. Pacheco; Brian T. Quinn; André J. W. van der Kouwe; Douglas N. Greve; Deborah Blacker; Marilyn S. Albert; et al. (NeuroImage, 2008)

MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. - Jorge Jovicich; Silvester Czanner; Xiao Han; David H. Salat; André J. W. van der Kouwe; Brian T. Quinn; Jenni Pacheco; Marilyn S. Albert; Ronald J. Killiany; Deborah Blacker; Ralph Paul Maguire; H. Diana Rosas; et al. (NeuroImage, 2009)

Harvard Aging Brain Study: Dataset and accessibility. - Alexander Dagley; Molly LaPoint; Willem Huijbers; Trey Hedden; Donald G. McLaren; Jasmeer P. Chhatwal; Kathryn V. Papp; Rebecca E. Amariglio; Deborah Blacker; Dorene M. Rentz; Keith A. Johnson; Reisa A. Sperling; et al. (NeuroImage, 2017)

Natural Language Processing to Detect Cognitive Concerns in Electronic Health Records Using Deep Learning. - Zhuoqiao Hong; Colin G. Magdamo; Yi-han Sheu; Prathamesh Mohite; Ayush Noori; Elissa M. Ye; Wendong Ge; Haoqi Sun; Laura Brenner; Gregory K. Robbins; Shibani Mukerji; Sahar Zafar; et al. (CoRR, 2020)

Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records. - Tanish Tyagi; Colin G. Magdamo; Ayush Noori; Zhaozhi Li; Xiao Liu; Mayuresh Deodhar; Zhuoqiao Hong; Wendong Ge; Elissa M. Ye; Yi-han Sheu; Haitham Alabsi; Laura Brenner; et al. (CoRR, 2021)

AI-assisted prediction of differential response to antidepressant classes using electronic health records. - Yi-han Sheu; Colin G. Magdamo; Matthew Miller; Sudeshna Das 001; Deborah Blacker; Jordan W. Smoller (npj Digit. Medicine, 2023)

A GPT-4o-powered framework for identifying cognitive impairment stages in electronic health records. - Yu Leng; Yingnan He; Samad Amini; Colin G. Magdamo; Ioannis Paschalidis; Shibani S. Mukerji; Lidia M. V. R. Moura; M. Brandon Westover; Ana-Maria Vranceanu; Christine S. Ritchie; Deborah Blacker; John R. Dickson; et al. (npj Digit. Medicine, 2025)

An Agentic AI Workflow for Detecting Cognitive Concerns in Real-world Data. - Jiazi Tian; Liqin Wang; Pedram J. Fard; Valdery Moura Junior; Deborah Blacker; Jennifer S. Haas; Chirag Patel; Shawn N. Murphy; Lidia M. V. R. Moura; Hossein Estiri (CoRR, 2025)

Evaluating GPT's Capability in Identifying Stages of Cognitive Impairment from Electronic Health Data. - Yu Leng; Yingnan He; Colin G. Magdamo; Ana-Maria Vranceanu; Christine S. Ritchie; Shibani S. Mukerji; Lidia M. V. R. Moura; John R. Dickson; Deborah Blacker; Sudeshna Das 001 (CoRR, 2025)