Natural Language Processing in Ubiquitous Healthcare

Scope

As part of the growth of ubiquitous computing we have seen the application of ubiquitous computing in healthcare with the aim of improving a patient’s health and quality of life.
Ubiquitous healthcare describes a seamless blend of technologies including cloud computing, mobile devices, embedded systems, software agents, plus environment and patient sensors and actuators.
Interacting with ubiquitous healthcare systems should be both enjoyable and intuitive for patients and there are significant human computer interaction (HCI) issues that need to be considered in developing effective, robust, unobtrusive and friendly user interfaces to ubiquitous healthcare systems.
One way to achieve this is through natural language interfaces and natural language processing (NLP) has received significant attention in areas such as personal assistants, intelligent tutors, question answering, search and information retrieval, sentiment analysis, recommender systems.
Relevant research in these areas has been published in many international forums including PervasiveHealth, Per-Health, the IEEE International Conference on E-health Networking, Application & Services, the ACM International Joint Conference on Pervasive and Ubiquitous Computing and many others. However, the full extent of the synergies between ubiquitous healthcare and NLP is yet to be realized and this theme issue aims to collect and consolidate innovative and high-quality research in NLP in ubiquitous healthcare.
This issue invites original scientific contributions in the form of theoretical foundations, experimental research, surveys, case studies, NLP-based techniques and ubiquitous healthcare systems.
Topics

The list of topics in scope for this issue includes, but is not limited to:
•Context-aware healthcare systems
•Development of interactive systems for emergency response
•Development of human-to-machine natural language instructions to ubiquitous healthcare systems
•Health and medical knowledge graphs
•Health information retrieval and extraction using NLP
•Pervasive networks and ubiquitous computing for wellness monitoring
•Data mining on clinical or social web data
•Machine learning on clinical or social web data
•Tools for clinical data interpretation and visualization
•Clinical decision support systems
•Speech-based, text-based, and multimodal interaction for healthcare applications
•Question answering technologies for healthcare applications
•Conversational agents for healthcare
•NLP techniques for personalization of healthcare
•Innovative NLP methods for capturing patient’s emotions from text
•NLP techniques for personalization of healthcare
•Natural Language Processing supporting interoperability in ubiquitous healthcare
•Social networks analytics for healthcare monitoring
•Ontological representations for ubiquitous healthcare
•Trends and challenges in NLP for ubiquitous healthcare

Submissions

All submissions should be prepared according to the Instructions for Authors at
https://www.springer.com/computer/hci/journal/779.
All contributions must not have been previously published or be under consideration for publication elsewhere.
A submission based on papers that have been previously published should include value-added extensions of at least 30% new material.
Authors are required to attach to the submitted paper their relevant, previously published articles and a summary document explaining the key differences between them and their submission for this theme issue.

Key dates

Submission deadline: July 2020
Notification of review: September 2020
Revision due: October 2020
Notification of Final Acceptance: December 2020
Expected Publication of the Special Issue: 2021

Editors

Mario Andrés Paredes-Valverde Instituto Tecnológico de Orizaba, Mexico mparedesv@ito-depi.edu.mx
Giner Alor-Hernández Instituto Tecnológico de Orizaba, Mexico galor@ito-depi.edu.mx
Rafael Valencia-García Universidad de Murcia, Spain valencia@um.es
Paolo Bellavista Università di Bologna paolo.bellavista@unibo.it