Scholars@Duke

• Research
• 

  Selected Grants

  • Deep learning-based image analysis for assessing real-time smoking risk awarded by National Institutes of Health 2018 - 2020
  • Deep learning-based image analysis for assessing real-time smoking risk awarded by National Institutes of Health 2018 - 2020
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Engelhard, M. M., & Kollins, S. H. (2019). The Many Channels of Screen Media Technology in ADHD: a Paradigm for Quantifying Distinct Risks and Potential Benefits.. Curr Psychiatry Rep, 21(9). https://doi.org/10.1007/s11920-019-1077-1
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    • Engelhard, M. M., Oliver, J. A., Henao, R., Hallyburton, M., Carin, L. E., Conklin, C., & McClernon, F. J. (2019). Identifying Smoking Environments From Images of Daily Life With Deep Learning.. Jama Netw Open, 2(8). https://doi.org/10.1001/jamanetworkopen.2019.7939
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    • Raman, S., Engelhard, M., & Kollins, S. H. (2019). Driving the Point Home: Novel Approaches to Mitigate Crash Risk for Patients With ADHD.. Pediatrics. https://doi.org/10.1542/peds.2019-0820
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    • Lunsford-Avery, J. R., Engelhard, M. M., Navar, A. M., & Kollins, S. H. (2018). Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk.. Sci Rep, 8(1). https://doi.org/10.1038/s41598-018-32402-5
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    • Engelhard, M., Xu, H., Carin, L., Oliver, J. A., Hallyburton, M., & McClernon, F. J. (2018). Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model.. Proc Mach Learn Res, 85, 312–331.
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    • Dandu, S. R., Engelhard, M. M., Qureshi, A., Gong, J., Lach, J. C., Brandt-Pearce, M., & Goldman, M. D. (2018). Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis.. Ieee Journal of Biomedical and Health Informatics, 22(1), 40–46. https://doi.org/10.1109/JBHI.2017.2773629
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    • Engelhard, M. M., Patek, S. D., Lach, J. C., & Goldman, M. D. (2018). Real-world walking in multiple sclerosis: Separating capacity from behavior.. Gait & Posture, 59, 211–216. https://doi.org/10.1016/j.gaitpost.2017.10.015
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    • Engelhard, M., Copley, C., Watson, J., Pillay, Y., Barron, P., & LeFevre, A. E. (2018). Optimising mHealth helpdesk responsiveness in South Africa: towards automated message triage.. Bmj Global Health, 3(Suppl 2). https://doi.org/10.1136/bmjgh-2017-000567
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    • LeFevre, A. E., Dane, P., Copley, C. J., Pienaar, C., Parsons, A. N., Engelhard, M., … Mohan, D. (2018). Unpacking the performance of a mobile health information messaging program for mothers (MomConnect) in South Africa: evidence on program reach and messaging exposure.. Bmj Global Health, 3(Suppl 2). https://doi.org/10.1136/bmjgh-2017-000583
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    • Engelhard, M. M., Patek, S. D., Sheridan, K., Lach, J. C., & Goldman, M. D. (2017). Remotely engaged: Lessons from remote monitoring in multiple sclerosis.. International Journal of Medical Informatics, 100, 26–31. https://doi.org/10.1016/j.ijmedinf.2017.01.006
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    • Engelhard, M. M., Schmidt, K. M., Engel, C. E., Brenton, J. N., Patek, S. D., & Goldman, M. D. (2016). The e-MSWS-12: improving the multiple sclerosis walking scale using item response theory.. Quality of Life Research : An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 25(12), 3221–3230. https://doi.org/10.1007/s11136-016-1342-2
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    • Cincotta, M. C., Engelhard, M. M., Stankey, M., & Goldman, M. D. (2016). Fatigue and fluid hydration status in multiple sclerosis: A hypothesis.. Multiple Sclerosis (Houndmills, Basingstoke, England), 22(11), 1438–1443. https://doi.org/10.1177/1352458516663854
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    • Engelhard, M. M., Dandu, S. R., Patek, S. D., Lach, J. C., & Goldman, M. D. (2016). Quantifying six-minute walk induced gait deterioration with inertial sensors in multiple sclerosis subjects.. Gait & Posture, 49, 340–345. https://doi.org/10.1016/j.gaitpost.2016.07.184
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    • Ribeiro, S., Shi, X., Engelhard, M., Zhou, Y., Zhang, H., Gervasoni, D., … Nicolelis, M. A. L. (2007). Novel experience induces persistent sleep-dependent plasticity in the cortex but not in the hippocampus.. Frontiers in Neuroscience, 1(1), 43–55. https://doi.org/10.3389/neuro.01.1.1.003.2007
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  • Conference Papers

    • Brenton, J. N., Engelhard, M., Woolbright, E., Koshiya, H., Herod, S. G., Engel, C. E., & Goldman, M. D. (2017). Continuous accelerometry as a measure of physical activity impairment in paediatric-onset multiple sclerosis subjects versus healthy controls. In Multiple Sclerosis Journal (Vol. 23, pp. 107–108). Paris, FRANCE: SAGE PUBLICATIONS LTD.
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    • Engelhard, M. M., Lach, J. C., Schmidt, K. M., Goldman, M. D., & Patek, S. D. (2016). Adaptive symptom reporting for mobile patient-reported disability assessment. In 2016 Ieee Wireless Health, Wh 2016 (pp. 172–179). https://doi.org/10.1109/WH.2016.7764573
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    • Engelhard, M. M., Dandu, S. R., Lach, J. C., Goldman, M. D., & Patek, S. D. (2015). Toward detection and monitoring of gait pathology using inertial sensors under rotation, scale, and offset invariant dynamic time warping. In Bodynets International Conference on Body Area Networks. https://doi.org/10.4108/eai.28-9-2015.2261503
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    • Gong, J., Engelhard, M. M., Goldman, M. D., & Lach, J. (2015). Correlations between inertial body sensor measures and clinical measures in multiple sclerosis. In Bodynets International Conference on Body Area Networks. https://doi.org/10.4108/eai.28-9-2015.2261504
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• Teaching & Mentoring
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  Recent Courses

  • MMCI 517: Applied Data Science 2019

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