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Applied Sciences
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Digital Therapeutics, Digital Twin and Mixed/Augmented Reality in Healthcare
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Digital Therapeutics, Digital Twin and Mixed/Augmented Reality in Healthcare

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 4109

Special Issue Editor

Prof. Dr. In Young Choi

E-Mail Website
Guest Editor
Department of Medical Informatics, The Catholic University of Korea, Seoul 06591, Korea
Interests: digital therapeutics; digital twin; mixed reality; augmented reality; Big Data; AI; medical informatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The pandemic has accelerated the transition to the digital age in the era of the Fourth Industrial Revolution, and various technologies are developing rapidly. In line with this trend, the digital healthcare industry of medical and ICT convergence is coming to light, as the medical industry is also shifting from treatment- and provider-oriented medical services to prevention- and consumer-oriented services. Digital therapeutics are software medical devices used to prevent, manage, and treat diseases based on scientific and clinical evidence on the mechanism of therapeutic action, which will require a multidisciplinary exploration to provide new treatment tools in our current society. The combination of digital twin technology, which allows for a better understanding of the characteristics of objects by virtually modeling and computer-simulating them, mixed reality and augmented reality, and healthcare will help people respond quickly to diseases by detecting and identifying problems before they occur in real-world environments and improving safety and efficiency. Improving healthcare services through the development of these technologies will be an innovative key to improving people's quality of life.

Therefore, we will focus on cases from the healthcare perspective with digital therapeutics, digital twin, and mixed/augmented reality as the subjects of this Special Issue. We look forward to your active submissions of comprehensive case study papers on all aspects, including theoretical and experimental studies and survey research on the development of the field.

Prof. Dr. In Young Choi
Guest Editor

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 submissions that pass pre-check are 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. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). 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 therapeutics
  • digital twin
  • Mixed Reality
  • Augmented Reality
  • MR
  • AR
  • healthcare
  • human–computer interaction
  • Internet of Things
  • Internet of Medical Things
  • IoT
  • IoMT
  • digital healthcare

Published Papers (2 papers)

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Research

10 pages, 1158 KiB  
Article
A Machine Learning Approach to Predict the Probability of Brain Metastasis in Renal Cell Carcinoma Patients
by Hyung Min Kim, Chang Wook Jeong, Cheol Kwak, Cheryn Song, Minyong Kang, Seong Il Seo, Jung Kwon Kim, Hakmin Lee, Jinsoo Chung, Eu Chang Hwang, Jae Young Park, In Young Choi and Sung-Hoo Hong
Appl. Sci. 2022, 12(12), 6174; https://0-doi-org.brum.beds.ac.uk/10.3390/app12126174 - 17 Jun 2022
Cited by 3 | Viewed by 1480
Abstract
Patients with brain metastasis (BM) have a better prognosis when it is detected early. However, current guidelines recommend brain imaging only when there are central nervous system symptoms or abnormal experimental values. Therefore, metastases are discovered later in asymptomatic patients. As a result, [...] Read more.
Patients with brain metastasis (BM) have a better prognosis when it is detected early. However, current guidelines recommend brain imaging only when there are central nervous system symptoms or abnormal experimental values. Therefore, metastases are discovered later in asymptomatic patients. As a result, there is a need for an algorithm that predicts the possibility of BM using clinical data and machine learning (ML). Data from 3153 patients with renal cell carcinoma (RCC) were collected from the 11-institution Korean Renal Cancer Study group (KRoCS) database. To predict BM, clinical information of 1282 patients was extracted from the database and used to compare the performance of six ML algorithms. The final model selection was based on the area under the receiver operating characteristic (AUROC) curve. After optimizing the hyperparameters for each model, the adaptive boosting (AdaBoost) model outperformed the others, with an AUROC of 0.716. We developed an algorithm to predict the probability of BM in patients with RCC. Using the developed predictive model, it is possible to avoid detection delays by performing computed tomography scans on potentially asymptomatic patients. Full article
(This article belongs to the Special Issue Digital Therapeutics, Digital Twin and Mixed/Augmented Reality in Healthcare)
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13 pages, 1489 KiB  
Article
Effectiveness of an mHealth Application to Overcome Problematic Smartphone Use: Comparing Mental Health of a Smartphone Control-Use Group and a Problematic-Use Group
by Mun Joo Choi, Sun Jung Lee, HyungMin Kim, Dai-Jin Kim and In Young Choi
Appl. Sci. 2021, 11(18), 8716; https://0-doi-org.brum.beds.ac.uk/10.3390/app11188716 - 18 Sep 2021
Cited by 2 | Viewed by 1778
Abstract
We developed an mHealth application that can help alleviate the problematic use of smartphones and allied psychological symptoms. This study observed the change in patterns of users’ problematic smartphone use, depression, and anxiety while using the mHealth application. We conducted this study from [...] Read more.
We developed an mHealth application that can help alleviate the problematic use of smartphones and allied psychological symptoms. This study observed the change in patterns of users’ problematic smartphone use, depression, and anxiety while using the mHealth application. We conducted this study from 9 January to 10 April 2019. The Korean Smartphone Addiction Proneness Scale for Adults, Generalized Anxiety Disorder Scale, and the Patient Health Questionnaire were measured at week 0, 8, 12. A post hoc test of Repeated Measurement Anova analysis and Linear Mixed Model analysis were used. Overall, 190 participants were allocated into two groups. Sixty-six were in the smartphone control-use group and 124 were in the problematic-use group. The study elucidated the difference between the two groups in terms of problematic smartphone use and depression and anxiety after 13 weeks of using the mHealth application. This study showed the use of the mHealth application reducing problematic smartphone use scores and negative symptoms such as anxiety and depression in the PSU group. The results can be used as the basis for similar qualitative studies to further resolve the problematic use of smartphones. Full article
(This article belongs to the Special Issue Digital Therapeutics, Digital Twin and Mixed/Augmented Reality in Healthcare)
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