Parisa Rashidi, Ph.D.
Affiliations: | 2011 | Computer Science | Washington State University, Pullman, WA, United States |
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Computer ScienceGoogle:
"Parisa Rashidi"Parents
Sign in to add mentorDiane J. Cook | grad student | 2011 | WSU | |
(Scaling activity discovery and recognition to large, complex datasets.) |
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Publications
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Davoudi A, Malhotra KR, Shickel B, et al. (2019) Intelligent ICU for Autonomous Patient Monitoring Using Pervasive Sensing and Deep Learning. Scientific Reports. 9: 8020 |
Shickel B, Loftus TJ, Adhikari L, et al. (2019) DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning. Scientific Reports. 9: 1879 |
Davoudi A, Wanigatunga AA, Kheirkhahan M, et al. (2019) Accuracy of Samsung Gear S Smartwatch for Activity Recognition: Validation Study. Jmir Mhealth and Uhealth. 7: e11270 |
Kheirkhahan M, Nair S, Davoudi A, et al. (2018) A Smartwatch-Based Framework for Real-Time and Online Assessment and Mobility Monitoring. Journal of Biomedical Informatics |
Mollalo A, Sadeghian A, Israel GD, et al. (2018) Machine learning approaches in GIS-based ecological modeling of the sand fly Phlebotomus papatasi, a vector of zoonotic cutaneous leishmaniasis in Golestan province, Iran. Acta Tropica. 188: 187-194 |
Bihorac A, Ozrazgat-Baslanti T, Ebadi A, et al. (2018) MySurgeryRisk: Development and Validation of a Machine-learning Risk Algorithm for Major Complications and Death After Surgery. Annals of Surgery |
Shickel B, Tighe PJ, Bihorac A, et al. (2017) Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis. Ieee Journal of Biomedical and Health Informatics |
Nickerson P, Baharloo R, Wanigatunga AA, et al. (2017) Transition Icons for Time Series Visualization and Exploratory Analysis. Ieee Journal of Biomedical and Health Informatics |
Wanigatunga AA, Nickerson PV, Manini TM, et al. (2016) Using symbolic aggregate approximation (SAX) to visualize activity transitions among older adults. Physiological Measurement. 37: 1981-1992 |
Thottakkara P, Ozrazgat-Baslanti T, Hupf BB, et al. (2016) Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications. Plos One. 11: e0155705 |