Murphy, Shawn N

A mega-analysis of genome-wide association studies for major depressive disorder

Major Depressive Disorder Working Group of the Psychiatric GWAS Consortium, Ripke, S., Wray, N. R., Lewis, C. M., Hamilton, S. P., Weissman, M. M., Breen, G., Byrne, E. M., Blackwood, D. H. R., Boomsma, D. I., et al. (2013) · Molecular Psychiatry

Genetic Associations and EpidemiologyBipolar Disorder and Treatment

Cited by 1,120

The Co-Morbidity Burden of Children and Young Adults with Autism Spectrum Disorders

Kohane, I. S., McMurry, A., Weber, G., MacFadden, D., Rappaport, L., Kunkel, L., Bickel, J., Wattanasin, N., Spence, S., Murphy, S., et al. (2012) · PLoS ONE

Autism Spectrum Disorder ResearchChild Nutrition and Feeding Issues

Cited by 562

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

Haendel, M. A., Chute, C. G., Bennett, T. D., Eichmann, D. A., Guinney, J., Kibbe, W. A., Payne, P. R. O., Pfaff, E. R., Robinson, P. N., Saltz, J. H., et al. (2021) · Journal of the American Medical Informatics Association

Research Data Management PracticesElectronic Health Records Systems

Cited by 553

Extracting principal diagnosis, co-morbidity and smoking status for asthma research: evaluation of a natural language processing system

Zeng, Q. T., Goryachev, S., Weiss, S., Sordo, M., Murphy, S. N., & Lazarus, R. (2006) · BMC Medical Informatics and Decision Making

Biomedical Text Mining and OntologiesMachine Learning in Healthcare

Cited by 360

The All of Us Research Program: Data quality, utility, and diversity

Ramirez, A. H., Sulieman, L., Schlueter, D. J., Halvorson, A., Qian, J., Ratsimbazafy, F., Loperena, R., Mayo, K., Basford, M., Deflaux, N., et al. (2022) · Patterns

Electronic Health Records SystemsEthics in Clinical Research

Cited by 352

Prenatal antidepressant exposure is associated with risk for attention-deficit hyperactivity disorder but not autism spectrum disorder in a large health system

Clements, C. C., Castro, V. M., Blumenthal, S. R., Rosenfield, H. R., Murphy, S. N., Fava, M., Erb, J. L., Churchill, S. E., Kaimal, A. J., Doyle, A. E., et al. (2015) · Molecular Psychiatry

Pregnancy and Medication ImpactPrenatal Substance Exposure Effects

Cited by 197

Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model

Perlis, R. H., Iosifescu, D. V., Castro, V. M., Murphy, S. N., Gainer, V. S., Minnier, J., Cai, T., Goryachev, S., Zeng, Q., Gallagher, P. J., et al. (2012) · Psychological Medicine

Treatment of Major DepressionMachine Learning in Healthcare

Cited by 193

An Electronic Health Records Study of Long-Term Weight Gain Following Antidepressant Use

Blumenthal, S. R., Castro, V. M., Clements, C. C., Rosenfield, H. R., Murphy, S. N., Fava, M., Weilburg, J. B., Erb, J. L., Churchill, S. E., Kohane, I. S., et al. (2014) · JAMA Psychiatry

Pharmacology and Obesity TreatmentTreatment of Major Depression

Cited by 151

Genetic Differences in the Immediate Transcriptome Response to Stress Predict Risk-Related Brain Function and Psychiatric Disorders

Arloth, J., Bogdan, R., Weber, P., Frishman, G., Menke, A., Wagner, K. V., Balsevich, G., Schmidt, M. V., Karbalai, N., Czamara, D., et al. (2015) · Neuron

Stress Responses and CortisolGenetic Associations and Epidemiology

Cited by 142

Psychiatric co‐morbidity is associated with increased risk of surgery in Crohn's disease

Ananthakrishnan, A. N., Gainer, V. S., Perez, R. G., Cai, T., Cheng, S. ‐., Savova, G., Chen, P., Szolovits, P., Xia, Z., De Jager, P. L., et al. (2013) · Alimentary Pharmacology & Therapeutics

Inflammatory Bowel DiseaseTryptophan and brain disorders

Cited by 122

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

Kohane, I. S., Aronow, B. J., Avillach, P., Beaulieu-Jones, B. K., Bellazzi, R., Bradford, R. L., Brat, G. A., Cannataro, M., Cimino, J. J., García-Barrio, N., et al. (2021) · Journal of Medical Internet Research

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 113

Results of a remotely delivered hypertension and lipid program in more than 10?000 patients across a diverse health care network.

Blood, A. J., Cannon, C. P., Gordon, W. J., Mailly, C., MacLean, T., Subramaniam, S., Tucci, M., Crossen, J., Nichols, H., Wagholikar, K. B., et al. (2023) · JAMA Cardiology

Telemedicine and Telehealth ImplementationBlood Pressure and Hypertension Studies

Cited by 108

Large-scale identification of patients with cerebral aneurysms using natural language processing

Castro, V. M., Dligach, D., Finan, S., Yu, S., Can, A., Abd-El-Barr, M., Gainer, V., Shadick, N. A., Murphy, S., Cai, T., et al. (2017) · Neurology

Machine Learning in HealthcareIntracranial Aneurysms: Treatment and Complications

Cited by 98

Biases introduced by filtering electronic health records for patients with “complete data.”

Weber, G. M., Adams, W. G., Bernstam, E. V., Bickel, J. P., Fox, K. P., Marsolo, K., Raghavan, V. A., Turchin, A., Zhou, X., Murphy, S. N., et al. (2017) · Journal of the American Medical Informatics Association

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 93

The association between lower educational attainment and depression owing to shared genetic effects? Results in ~25 000 subjects

Peyrot, W. J., Lee, S. H., Milaneschi, Y., Abdellaoui, A., Byrne, E. M., Esko, T., de Geus, E. J. C., Hemani, G., Hottenga, J. J., Kloiber, S., et al. (2015) · Molecular Psychiatry

Genetic Associations and EpidemiologyNeurotransmitter Receptor Influence on Behavior

Cited by 84

Establishing responsible use of AI guidelines: a comprehensive case study for healthcare institutions

Saenz, A. D., Mass General Brigham AI Governance Committee, McCoy, T., Mantha, A. B., Martin, R., Damiano, R., Adair, D., Heaney, D., Sisodia, R., Park, L., et al. (2024) · npj Digital Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 62

Identification of subjects with polycystic ovary syndrome using electronic health records

Castro, V., Shen, Y., Yu, S., Finan, S., Pau, C. T., Gainer, V., Keefe, C. C., Savova, G., Murphy, S. N., Cai, T., et al. (2015) · Reproductive Biology and Endocrinology

Ovarian function and disordersMedical Coding and Health Information

Cited by 51

Extraction of ejection fraction from echocardiography notes for constructing a cohort of patients having heart failure with reduced ejection fraction (HFrEF)

Wagholikar, K. B., Fischer, C. M., Goodson, A., Herrick, C. D., Rees, M., Toscano, E., MacRae, C. A., Scirica, B. M., Desai, A. S., & Murphy, S. N. (2018) · Journal of Medical Systems

Artificial Intelligence in HealthcareBiomedical Text Mining and Ontologies

Cited by 27

High-throughput phenotyping with temporal sequences

Estiri, H., Strasser, Z. H., & Murphy, S. N. (2021) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 26

Feasibility of studying brain morphology in major depressive disorder with structural magnetic resonance imaging and clinical data from the electronic medical record: A pilot study

Hoogenboom, W. S., Perlis, R. H., Smoller, J. W., Zeng-Treitler, Q., Gainer, V. S., Murphy, S. N., Churchill, S. E., Kohane, I. S., Shenton, M. E., & Iosifescu, D. V. (2013) · Psychiatry Research: Neuroimaging

Treatment of Major DepressionFunctional Brain Connectivity Studies

Cited by 13