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Intelligent Digital Health Interventions
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Intelligent Digital Health Interventions

A special issue of Digital (ISSN 2673-6470).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 7170

Special Issue Editors

Dr. Andreas Triantafyllidis

E-Mail Website
Guest Editor
Centre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece
Interests: mobile health; medical informatics; pervasive computing; artificial intelligence; computerised decision support
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Mariusz Duplaga

E-Mail Website
Guest Editor
Department of Health Promotion and e-Health, Institute of Public Health, Faculty of Health Sciences, Jagiellonian University Medical College, Skawińska Str. 8, 31-066 Krakow, Poland
Interests: e-health; telemedicine; digital health; public health; health promotion; health literacay; digital health literecy; respiratory medicine
Special Issues, Collections and Topics in MDPI journals
Dr. Konstantinos Votis

E-Mail Website
Guest Editor
Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
Interests: Internet of Things; security of data; health care; blockchains; diseases; learning (artificial intelligence); data privacy; patient monitoring; cryptography; decision support systems; mobile robots; neural nets; authorisation; computer network security
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleague,

Digital health technology, including modalities such as mobile apps, Internet-linked systems, electronic health records, and monitoring sensors, shows enormous potential to transform healthcare by supporting independent living and self-management, reducing health care costs, and providing significant health outcomes for both patients and medical professionals. The challenge now is to take advantage of the knowledge generated through the collection, processing, and evaluation of clinical, sensed, and behavioral data, in order to support remote medical management and coach patients where required. Toward this end, new intelligent digital health interventions based on tools and algorithms for computerized decision support and machine learning need to be carefully designed, developed, and deployed in real-world settings.

The Special Issue on Intelligent Digital Health Interventions aims to present the latest advances in the application of digital health technologies. Theoretical and practical aspects related to digital health, reviews, as well as interventions targeting the COVID-19 pandemic period are appropriate.

Topics of interest include, but are not limited to:

Mobile and pervasive computing;

  • Machine learning approaches;
  • Real-world digital health interventions;
  • Decision support systems;
  • Knowledge discovery in intelligent health systems;
  • Natural language processing;
  • Mining of electronic health records;
  • Security of health information;
  • Medical devices, smart biosensors, and sensor networks;
  • Internet of Things;
  • Augmented or virtual reality applications;
  • Usability and patient satisfaction;
  • Health education;
  • Robotics interventions;
  • Digital health technologies designed specifically for children, seniors, or people with chronic disease.

Dr. Andreas Triantafyllidis
Prof. Dr. Mariusz Duplaga
Dr. Konstantinos Votis
Guest Editors

Manuscript Submission Information 

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Digital is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. Currently, publication in this open access journal is free. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Digital health
  • Machine learning
  • Decision support systems
  • Mobile computing
  • Pervasive health
  • Knowledge discovery
  • Internet of Things
  • Intelligent sensors
  • Medical interventions

Published Papers (2 papers)

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Research

16 pages, 2340 KiB  
Article
The Development of a Clinical Decision-Support Web-Based Tool for Predicting the Risk of Gastrointestinal Cancer in Iron Deficiency Anaemia—The IDIOM App
by Orouba Almilaji, Vegard Engen, Jonathon Snook and Sharon Docherty
Digital 2022, 2(1), 104-119; https://doi.org/10.3390/digital2010007 - 18 Mar 2022
Cited by 2 | Viewed by 2536
Abstract
To facilitate the clinical use of an algorithm for predicting the risk of gastrointestinal malignancy in iron deficiency anaemia—the IDIOM score, a software application has been developed, with a view to providing free and simple access to healthcare professionals in the UK. A [...] Read more.
To facilitate the clinical use of an algorithm for predicting the risk of gastrointestinal malignancy in iron deficiency anaemia—the IDIOM score, a software application has been developed, with a view to providing free and simple access to healthcare professionals in the UK. A detailed requirements analysis for intended users of the application revealed the need for an automated decision-support tool in which anonymised, individual patient data is entered and gastrointestinal cancer risk is calculated and displayed immediately, which lends itself to use in busy clinical settings. Human-centred design was employed to develop the solution, focusing on the users and their needs, whilst ensuring that they are provided with sufficient details to appropriately interpret the risk score. The IDIOM App has been developed using R Shiny as a web-based application enabling access from different platforms with updates that can be carried out centrally through the host server. The application has been evaluated through literature search, internal/external validation, code testing, risk analysis, and usability assessments. Legal notices, contact system with research and maintenance teams, and all the supportive information for the application such as description of the population and intended users have been embedded within the application interface. With the purpose of providing a guide of developing standalone software medical devices in academic setting, this paper aims to present the theoretical and practical aspects of developing, writing technical documentation, and certifying standalone software medical devices using the case of the IDIOM App as an example. Full article
(This article belongs to the Special Issue Intelligent Digital Health Interventions)
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8 pages, 618 KiB  
Communication
Comparison between Self-Reported and Accelerometer-Measured Physical Activity in Young versus Older Children
by Andreas Triantafyllidis, Anastasios Alexiadis, Konstantinos Soutos, Thomas Fischer, Konstantinos Votis and Dimitrios Tzovaras
Digital 2021, 1(2), 103-110; https://doi.org/10.3390/digital1020008 - 9 Apr 2021
Cited by 2 | Viewed by 3220
Abstract
Physical inactivity in children is a major public health challenge, for which valid physical activity assessment tools are needed. Wearable devices provide a means for objective assessment of children’s physical activity, but they are often not adopted because of issues such as cost, [...] Read more.
Physical inactivity in children is a major public health challenge, for which valid physical activity assessment tools are needed. Wearable devices provide a means for objective assessment of children’s physical activity, but they are often not adopted because of issues such as cost, comfort, and privacy. In this context, self-reporting tools could be employed, but their validity in relation to a child’s age is understudied. We present the agreement of one of the most popular self-reporting tools, the Physical Activity Questionnaire for Children (PAQ-C) with accelerometer-measured physical activity in 9-year-old versus 12-year-old children, wearing an accelerometer-based wearable device for seven consecutive days. We study the relationship between the PAQ-C and accelerometer scores using Spearman’s rank correlation coefficients and Bland–Altman plots in a sample of 131 children included for analysis. Overall, there was correlation between PAQ-C score and physical activity measures for the 12-year-old children (rho = 0.47 for total physical activity, rho = 0.43 for moderate-to-vigorous physical activity, rho = 0.41 for steps, p < 0.01), but not for the 9-year-old children (rho = 0.08 for total physical activity, rho = 0.21 for moderate-to-vigorous physical activity, rho = 0.19 for steps, p > 0.05). All PAQ-C items other than item 3 (activity at recess) did not reach significance in correlation with accelerometry for the 9-year-old children (p > 0.05). Therefore, the use of wearable devices for more objective assessment of physical activity in younger children should be preferred. Full article
(This article belongs to the Special Issue Intelligent Digital Health Interventions)
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