scholarly journals EREBOTS: Privacy-Compliant Agent-Based Platform for Multi-Scenario Personalized Health-Assistant Chatbots

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 666
Author(s):  
Davide Calvaresi ◽  
Jean-Paul Calbimonte ◽  
Enrico Siboni ◽  
Stefan Eggenschwiler ◽  
Gaetano Manzo ◽  
...  
Keyword(s):  
Breast Cancer Survivors ◽  
Physical Conditioning ◽  
Privacy Management ◽  
Web Interface ◽  
Agent Based ◽  
Multimodal Interactions ◽  
Physical Exercises ◽  
Health Related ◽  
Health Assistant ◽  
Personalized Health

Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and are becoming ingrained into humans’ habits due to factors including (i) the availability of mobile devices such as smartphones and tablets, (ii) the increasingly engaging nature of chatbot interactions, (iii) the release of dedicated APIs from messaging platforms, and (iv) increasingly complex AI-based mechanisms to power the bots’ behaviors. Nevertheless, most of the modern chatbots rely on state machines (implementing conversational rules) and one-fits-all approaches, neglecting personalization, data-stream privacy management, multi-topic management/interconnection, and multimodal interactions. Objective. This work addresses the challenges above through an agent-based framework for chatbot development named EREBOTS. Methods. The foundations of the framework are based on the implementation of (i) multi-front-end connectors and interfaces (i.e., Telegram, dedicated App, and web interface), (ii) enabling the configuration of multi-scenario behaviors (i.e., preventive physical conditioning, smoking cessation, and support for breast-cancer survivors), (iii) online learning, (iv) personalized conversations and recommendations (i.e., mood boost, anti-craving persuasion, and balance-preserving physical exercises), and (v) responsive multi-device monitoring interface (i.e., doctor and admin). Results. EREBOTS has been tested in the context of physical balance preservation in social confinement times (due to the ongoing pandemic). Thirteen individuals characterized by diverse age, gender, and country distribution have actively participated in the experimentation, reporting advancements in the physical balance and overall satisfaction of the interaction and exercises’ variety they have been proposed.

scholarly journals Assisting humans in privacy management: an agent-based approach

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
A. Can Kurtan ◽  
Pınar Yolum
Keyword(s):  
Online Social Networks ◽  
Online Social Network ◽  
Real Life ◽  
Privacy Management ◽  
Agent Based ◽  
Image Sharing ◽  
Privacy Preferences ◽  
Privacy Settings ◽  
Privacy Setting ◽  
Sharing Behavior

AbstractImage sharing is a service offered by many online social networks. In order to preserve privacy of images, users need to think through and specify a privacy setting for each image that they upload. This is difficult for two main reasons: first, research shows that many times users do not know their own privacy preferences, but only become aware of them over time. Second, even when users know their privacy preferences, editing these privacy settings is cumbersome and requires too much effort, interfering with the quick sharing behavior expected on an online social network. Accordingly, this paper proposes a privacy recommendation model for images using tags and an agent that implements this, namely pelte. Each user agent makes use of the privacy settings that its user have set for previous images to predict automatically the privacy setting for an image that is uploaded to be shared. When in doubt, the agent analyzes the sharing behavior of other users in the user’s network to be able to recommend to its user about what should be considered as private. Contrary to existing approaches that assume all the images are available to a centralized model, pelte is compatible to distributed environments since each agent accesses only the privacy settings of the images that the agent owner has shared or those that have been shared with the user. Our simulations on a real-life dataset shows that pelte can accurately predict privacy settings even when a user has shared a few images with others, the images have only a few tags or the user’s friends have varying privacy preferences.

Tai Chi Chuan, Health-Related Quality of Life and Mediators of Inflammation in Breast Cancer Survivors

2010 ◽  
Vol 42 ◽  
pp. 162
Author(s):  
Lisa K. Sprod ◽  
Oxana G. Palesh ◽  
Luke J. Peppone ◽  
Michelle C. Janelsins-Benton ◽  
Charles E. Heckler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Breast Cancer Survivors ◽  
Tai Chi ◽  
Health Related Quality ◽  
Tai Chi Chuan ◽  
Mediators Of Inflammation ◽  
Related Quality ◽  
Health Related

Health-Related Quality of Life in a Predictive Model for Mortality in Older Breast Cancer Survivors

2018 ◽  
Vol 66 (6) ◽  
pp. 1115-1122 ◽  
Author(s):  
Clark DuMontier ◽  
Kerri M. Clough-Gorr ◽  
Rebecca A. Silliman ◽  
Andreas E. Stuck ◽  
André Moser
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Cancer Survivors ◽  
Predictive Model ◽  
Breast Cancer Survivors ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

scholarly journals The Relationship Between Health-Related Quality of Life and Saliva C-Reactive Protein and Diurnal Cortisol Rhythm in Latina Breast Cancer Survivors and Their Informal Caregivers: A Pilot Study

2020 ◽  
pp. 104365962092653
Author(s):  
Thaddeus W. W. Pace ◽  
Terry A. Badger ◽  
Chris Segrin ◽  
Alla Sikorskii ◽  
Tracy E. Crane
Keyword(s):  
Breast Cancer ◽  
Quality Of Life ◽  
Cancer Survivors ◽  
Breast Cancer Survivors ◽  
Health Related Quality ◽  
C Reactive Protein ◽  
Reactive Protein ◽  
Related Quality ◽  
Health Related

Introduction: To date, no study has explored associations between objective stress-related biomarkers (i.e., inflammatory markers, diurnal rhythm of cortisol) and health-related quality of life (HRQOL) in Latina breast cancer survivors and their informal caregivers (i.e., family, friends). Method: This cross-sectional feasibility study assessed saliva C-reactive protein, saliva diurnal cortisol rhythm (cortisol slope), and self-reported HRQOL (psychological, physical, and social domains) in 22 Latina survivor–caregiver dyads. Feasibility was defined as ≥85% samples collected over 2 days (on waking, in afternoon, and in evening). Associations between biomarkers and HRQOL were examined with correlational analyses. Results: Collection of saliva was feasible. Strongest associations were observed between survivor evening cortisol (as well as cortisol slope) and fatigue, a component of physical HRQOL. Discussion: Associations presented may help promote investigations of mechanisms linking stress-related biomarkers and HRQOL in Latina breast cancer survivor–caregiver dyads, which will facilitate development of culturally congruent interventions for this underserved group.

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