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A Protocol-Driven, Digital Conversational Agent at the Hospital Bedside to Support Nurse Teams and to Mitigate Delirium and Falls Risk

A Protocol-Driven, Digital Conversational Agent at the Hospital Bedside to Support Nurse Teams and to Mitigate Delirium and Falls Risk

RealMillbrae, CA,United States866 6964victor@care.coachhttp://orcid.org/0000-0001-7493-1981WexlerSharonPhD, RN2DruryLinPhD, RN2WangBrittanyMA11care.coach corporationMillbrae, CAUnited States2Pace UniversityNew York, NYUnited StatesCorresponding Author: Victor Wang

Victor Wang, Sharon Wexler, Lin Drury, Brittany Wang

iproc 2018;4(2):e11883

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study

Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study

The times series passed into Google Correlate are the national flu time series and the regional flu time series (Brittany region) obtained from the French Sentinelles network (see below).

Canelle Poirier, Audrey Lavenu, Valérie Bertaud, Boris Campillo-Gimenez, Emmanuel Chazard, Marc Cuggia, Guillaume Bouzillé

JMIR Public Health Surveill 2018;4(4):e11361

Statistical Issues and Lessons Learned From COVID-19 Clinical Trials With Lopinavir-Ritonavir and Remdesivir

Statistical Issues and Lessons Learned From COVID-19 Clinical Trials With Lopinavir-Ritonavir and Remdesivir

We take the three randomized clinical trials conducted by Cao et al [12] on lopinavir-ritonavir and by Wang et al [13] and Beigel et al [14] on remdesivir as examples to illustrate statistical issues and lessons learned, as they have drawn great attention in

Guosheng Yin, Chenyang Zhang, Huaqing Jin

JMIR Public Health Surveill 2020;6(3):e19538

Depression Risk Prediction for Chinese Microblogs via Deep-Learning Methods: Content Analysis

Depression Risk Prediction for Chinese Microblogs via Deep-Learning Methods: Content Analysis

This study represents an extension of the study of Wang et al [16], who presented an annotated dataset of Chinese microblogs for depression risk prediction and compared four machine-learning methods, including the deep-learning method bidirectional encoder

Xiaofeng Wang, Shuai Chen, Tao Li, Wanting Li, Yejie Zhou, Jie Zheng, Qingcai Chen, Jun Yan, Buzhou Tang

JMIR Med Inform 2020;8(7):e17958