. A Machine Learning Approach to Identifying the Thought Markers of Suicidal Subjects: A Prospective Multicenter Trial. Suicide and Life-Threatening Behavior. 2017; 47:112-121.
. A Controlled Trial Using Natural Language Processing to Examine the Language of Suicidal Adolescents in the Emergency Department. Suicide and Life-Threatening Behavior. 2016; 46:154-159.
. Methodological Issues in Predicting Pediatric Epilepsy Surgery Candidates Through Natural Language Processing and Machine Learning. Biomedical Informatics Insights. 2016; 8:11-18.
. Assessing the similarity of surface linguistic features related to epilepsy across pediatric hospitals. Journal of the American Medical Informatics Association : JAMIA. 2014; 21:866-870.
. Sentiment Analysis of Suicide Notes: A Shared Task. Biomedical Informatics Insights. 2012; 5:3-16.
. Nebulized Ipratropium Decreases Hospitalization Rate of Children with Severe Asthma • 389. Pediatric Research. 1998; 43:69.
. Analyses of GWAS signal using GRIN identify additional genes contributing to suicidal behavior. Communications Biology. 2024; 7:1360.
. High dimensional predictions of suicide risk in 4.2 million US Veterans using ensemble transfer learning. Scientific Reports. 2024; 14:1793.
. Early Identification of Candidates for Epilepsy Surgery: A Multicenter, Machine Learning, Prospective Validation Study. Neurology. 2024; 102:e208048.
. Addressing the Pediatric Mental Health Crisis: Moving from a Reactive to a Proactive System of Care. The Journal of Pediatrics. 2024; 265:113479.
. Using iterative random forest to find geospatial environmental and Sociodemographic predictors of suicide attempts. Frontiers in Psychiatry. 2023; 14:1178633.
. Developmental Epidemiology of Pediatric Anxiety Disorders. Child and Adolescent Psychiatric Clinics of North America. 2023; 32:511-530.
. Automated, machine learning-based alerts increase epilepsy surgery referrals: A randomized controlled trial. Epilepsia. 2023; 64:1791-1799.
. (2023) Application of Unified Medical Language System (UMLS) to Standardize Pediatric Drug Data. Institute of Electrical and Electronics Engineers (IEEE). 00:753-755.
. Identification of Novel, Replicable Genetic Risk Loci for Suicidal Thoughts and Behaviors Among US Military Veterans. JAMA Psychiatry. 2023; 80:135-145.
. Implementation of Machine Learning Pipelines for Clinical Practice: Development and Validation Study. JMIR Medical Informatics. 2022; 10:e37833.
. Toward Suicidal Ideation Detection with Lexical Network Features and Machine Learning. Northeast Journal of Complex Systems. 2022; 4.
. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors. Biological Psychiatry. 2022; 91:313-327.
. Early identification of epilepsy surgery candidates: A multicenter, machine learning study. Acta Neurologica Scandinavica. 2021; 144:41-50.
. Cystic Fibrosis Point of Personalized Detection (CFPOPD): An Interactive Web Application. JMIR Medical Informatics. 2020; 8:e23530.
. A Feasibility Study Using a Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in Adolescent Therapy Sessions. International Journal of Environmental Research and Public Health. 2020; 17:E8187.
. A Machine Learning Approach to Identifying Changes in Suicidal Language. Suicide and Life-Threatening Behavior. 2020; 50:939-947.