Literature DB >> 31135345

Health Care Chatbots Are Here to Help.

Mary Bates.   

Abstract

Say hello to molly, Florence, and Ada-they're just a few of the helpful, smart algorithm powered chatbots taking their place in health care. Chatbots are computer programs designed to carry on a dialogue with people, assisting them via text messages, applications, or instant messaging. Essentially, instead of having a conversation with a person, the user talks with a bot that's powered by basic rules or artificial intelligence. Chatbots are already widely used to support, expedite, and improve processes in other industries, such as retail, and now, the technology is gaining traction in health care, where it is helping patients and providers perform myriad tasks.

Entities:  

Mesh:

Year:  2019        PMID: 31135345     DOI: 10.1109/MPULS.2019.2911816

Source DB:  PubMed          Journal:  IEEE Pulse        ISSN: 2154-2287            Impact factor:   0.924


  6 in total

1.  Self-Diagnosis through AI-enabled Chatbot-based Symptom Checkers: User Experiences and Design Considerations.

Authors:  Yue You; Xinning Gui
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  A Review of Artificial Intelligence and Robotics in Transformed Health Ecosystems.

Authors:  Kerstin Denecke; Claude R Baudoin
Journal:  Front Med (Lausanne)       Date:  2022-07-06

Review 3.  Health-focused conversational agents in person-centered care: a review of apps.

Authors:  Pritika Parmar; Jina Ryu; Shivani Pandya; João Sedoc; Smisha Agarwal
Journal:  NPJ Digit Med       Date:  2022-02-17

4.  Assessing the Topics and Motivating Factors Behind Human-Social Chatbot Interactions: Thematic Analysis of User Experiences.

Authors:  Vivian P Ta-Johnson; Carolynn Boatfield; Xinyu Wang; Esther DeCero; Isabel C Krupica; Sophie D Rasof; Amelie Motzer; Wiktoria M Pedryc
Journal:  JMIR Hum Factors       Date:  2022-10-03

5.  Effectiveness of Using Voice Assistants in Learning: A Study at the Time of COVID-19.

Authors:  María Consuelo Sáiz-Manzanares; Raúl Marticorena-Sánchez; Javier Ochoa-Orihuel
Journal:  Int J Environ Res Public Health       Date:  2020-08-04       Impact factor: 3.390

6.  Agreement and Reliability Analysis of Machine Learning Scaling and Wireless Monitoring in the Assessment of Acute Proximal Weakness by Experts and Non-Experts: A Feasibility Study.

Authors:  Eunjeong Park; Kijeong Lee; Taehwa Han; Hyo Suk Nam
Journal:  J Pers Med       Date:  2022-01-01
  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.