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Toward Detection and Monitoring of Gait Pathology using Inertial Sensors under Rotation, Scale, and Offset Invariant Dynamic Time Warping.

, , , , и . BODYNETS, ICST, (2015)

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SpanPredict: Extraction of Predictive Document Spans with Neural Attention., , , , , и . NAACL-HLT, стр. 5234-5258. Association for Computational Linguistics, (2021)Neural Conditional Event Time Models., , , и . MLHC, том 126 из Proceedings of Machine Learning Research, стр. 223-244. PMLR, (2020)Toward Detection and Monitoring of Gait Pathology using Inertial Sensors under Rotation, Scale, and Offset Invariant Dynamic Time Warping., , , , и . BODYNETS, ICST, (2015)Determining physiological significance of inertial gait features in multiple sclerosis., , , и . BSN, стр. 266-271. IEEE, (2016)Adaptive Discretization for Event PredicTion (ADEPT)., , , , и . AISTATS, том 238 из Proceedings of Machine Learning Research, стр. 1351-1359. PMLR, (2024)Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model., , , , , и . MLHC, том 85 из Proceedings of Machine Learning Research, стр. 312-331. PMLR, (2018)Correlations between Inertial Body Sensor Measures and Clinical Measures in Multiple Sclerosis., , , и . BODYNETS, ICST, (2015)Disentangling Whether from When in a Neural Mixture Cure Model for Failure Time Data., и . AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 9571-9581. PMLR, (2022)A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis., , , , , , , , , и . J. Biomed. Informatics, (2024)Relationship between kernel density function estimates of gait time series and clinical data., , , и . BHI, стр. 329-332. IEEE, (2017)