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Special Issue "Digital Transformation in Healthcare"

A special issue of Healthcare (ISSN 2227-9032). This special issue belongs to the section "Artificial Intelligence in Medicine".

Deadline for manuscript submissions: closed (15 December 2021) | Viewed by 31848

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. Marco P. Soares dos Santos
E-Mail Website
Guest Editor
Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal
Interests: bioelectronic implants; sensors for medical devices; biophysical stimulation of biological tissues; energy harvesting to power intracorporeal medical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This issue aims to provide a revealing overview of the impact of advanced computation and instrumentation on healthcare. A worldwide increasing trend is driving innovation for a new era of multifunctional technologies with the ability to autonomously perform intensive therapeutic actuation, physiologic monitoring, digital processing, and communication operations. Products and services are being researched to increasingly incorporate computational capabilities. Research on healthcare is nowadays performed on a multidisciplinary basis, comprising computational engineering, biomedicine, biomedical engineering, electronic engineering, and automation engineering, among other areas. This Special Issue aims to disseminate cutting-edge research focused on ten topics: (1) personalized healthcare; (2) big data in healthcare; (3) predictive healthcare; (4) virtual reality in healthcare; (5) telemedicine; (6) artificial intelligence in healthcare; (7) bioelectronic medicine; (8) innovative medical devices—wearable medical devices and bioelectronic/instrumented implants; (9) modelling and simulation in healthcare; (10) energy harvesting to power medical devices. This interdisciplinary forum encourages the submission of original research, reviews, short reports, and opinion papers.

Dr. Marco P. Soares dos Santos
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. Healthcare is an international peer-reviewed open access monthly 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 1800 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

  • Personalized healthcare
  • Big data in healthcare
  • Predictive healthcare
  • Virtual reality in healthcare
  • Modelling and simulation
  • Bioelectronic medicine
  • Telemedicine
  • Artificial intelligence
  • Medical devices
  • Energy harvesting

Published Papers (16 papers)

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Research

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Article
A Design Approach to Optimise Secure Remote Three-Dimensional (3D) Printing: A Proof-of-Concept Study towards Advancement in Telemedicine
Healthcare 2022, 10(6), 1114; https://doi.org/10.3390/healthcare10061114 - 15 Jun 2022
Viewed by 934
Abstract
Telemedicine is defined as the delivery of healthcare services at a distance using electronic means. The incorporation of 3D printing in the telemedicine cycle could result in pharmacists designing and manufacturing personalised medicines based on the electronic prescription received. Even with the advantages [...] Read more.
Telemedicine is defined as the delivery of healthcare services at a distance using electronic means. The incorporation of 3D printing in the telemedicine cycle could result in pharmacists designing and manufacturing personalised medicines based on the electronic prescription received. Even with the advantages of telemedicine, numerous barriers to the uptake hinder the wider uptake. Of particular concern is the cyber risk associated with the remote digital transfer of the computer-aided design (CAD) file (acting as the electronic prescription) to the 3D printer and the reproducibility of the resultant printed medicinal products. This proof-of-concept study aimed to explore the application of secure remote 3D printing of model solid dosage forms using the patented technology, DEFEND3D, which is designed to enhance cybersecurity and intellectual property (IP) protection. The size, shape, and colour of the remote 3D-printed model medicinal products were also evaluated to ensure the end-product quality was user-focused. Thermoplastic polyurethane (TPU) and poly(lactic) acid (PLA) were chosen as model polymers due to their flexibility in preventing breakage printing and ease of printing with fused deposition modelling (FDM). Our work confirmed the potential of secure remote 3D (FDM) printing of prototype solid dosage forms resulting in products with good reproducibility, resolution, and quality towards advancements in telemedicine and digital pharmacies. The limitation of the work presented here was the use of model polymers and not pharmaceutically relevant polymers. Further work could be conducted using the same designs chosen in this study with pharmaceutically relevant polymers used in hot-melt extrusion (HME) with shown suitability for FDM 3D printing. However, it should be noted that any challenges that may occur with pharmaceutically relevant polymers are likely to be related to the polymer’s printability and printer choice as opposed to the ability of the CAD file to be transferred to the printer remotely. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Modeling Patient Flow in an Emergency Department under COVID-19 Pandemic Conditions: A Hybrid Modeling Approach
Healthcare 2022, 10(5), 840; https://doi.org/10.3390/healthcare10050840 - 02 May 2022
Cited by 1 | Viewed by 871
Abstract
Emergency departments (EDs) had to considerably change their patient flow policies in the wake of the COVID-19 pandemic. Such changes affect patient crowding, waiting time, and other qualities related to patient care and experience. Field experiments, surveys, and simulation models can generally offer [...] Read more.
Emergency departments (EDs) had to considerably change their patient flow policies in the wake of the COVID-19 pandemic. Such changes affect patient crowding, waiting time, and other qualities related to patient care and experience. Field experiments, surveys, and simulation models can generally offer insights into patient flow under pandemic conditions. This paper provides a thorough and transparent account of the development of a multi-method simulation model that emulates actual patient flow in the emergency department under COVID-19 pandemic conditions. Additionally, a number of performance measures useful to practitioners are introduced. A conceptual model was extracted from the main stakeholders at the case hospital through incremental elaboration and turned into a computational model. Two agent types were mainly modeled: patient and rooms. The simulated behavior of patient flow was validated with real-world data (Smart Crowding) and was able to replicate actual behavior in terms of patient occupancy. In order to further the validity, the study recommends several phenomena to be studied and included in future simulation models such as more agents (medical doctors, nurses, beds), delays due to interactions with other departments in the hospital and treatment time changes at higher occupancies. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
The Use of Modern Technologies by Dentists in Poland: Questionnaire among Polish Dentists
Healthcare 2022, 10(2), 225; https://doi.org/10.3390/healthcare10020225 - 25 Jan 2022
Viewed by 1423
Abstract
Background: From one year to another, dentists have access to more procedures using modern techniques. Many of them can improve the effectiveness of dental procedures and frequently facilitate and accelerate them. Objectives: Technically advanced devices are an important part of modern dentistry. Over [...] Read more.
Background: From one year to another, dentists have access to more procedures using modern techniques. Many of them can improve the effectiveness of dental procedures and frequently facilitate and accelerate them. Objectives: Technically advanced devices are an important part of modern dentistry. Over the years, there were developed technologies like ultrasounds, lasers, air abrasion, ozonotherapy, caries diagnostic methods, chemomechanical caries removal (CMCR), pulp vitality tests, computer-controlled local anesthetic delivery (CCLAD). The aim of this study was to investigate the requirement of Polish dentists for such technologies. Methods: An anonymous questionnaire was posted on a social media group of dentists from Poland. 187 responses were obtained. Results: It turned out that almost every respondent uses ultrasounds, but other technologies are not as popular. 43% use CCLAD, 33% use diagnostic methods, 28% use air abrasion, 25% use dental lasers, 21% use CMCR, 18% use pulp vitality tests and 6% use ozonotherapy. The most common reason for not using the aforementioned technologies were their high cost and the sufficient effectiveness of raditional methods. There was a correlation between use of a dental laser and CCLAD and size of office, CMCR use and dentists’ work time and air abrasion use and gender. Many dentists claim that they will try one of the modern technologies in the future. Conclusions: It can be concluded that Polish dentists tend to use ultrasounds and CCLAD more than any other technology. In the future this may change, so more studies in this topic are needed. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Impact of a Digital Intervention for Literacy in Depression among Portuguese University Students: A Randomized Controlled Trial
Healthcare 2022, 10(1), 165; https://doi.org/10.3390/healthcare10010165 - 15 Jan 2022
Viewed by 990
Abstract
Digital interventions are important tools to promote mental health literacy among university students. “Depression in Portuguese University Students” (Depressão em Estudantes Universitários Portugueses, DEEP) is an audiovisual intervention describing how symptoms can be identified and what possible treatments can be applied. The aim [...] Read more.
Digital interventions are important tools to promote mental health literacy among university students. “Depression in Portuguese University Students” (Depressão em Estudantes Universitários Portugueses, DEEP) is an audiovisual intervention describing how symptoms can be identified and what possible treatments can be applied. The aim of this study was to evaluate the impact of this intervention. A random sample of 98 students, aged 20–38 years old, participated in a 12-week study. Participants were recruited through social media by the academic services and institutional emails of two Portuguese universities. Participants were contacted and distributed into four study groups (G1, G2, G3 and G4): G1 received the DEEP intervention in audiovisual format; G2 was given the DEEP in text format; G3 received four news articles on depression; G4 was the control group. A questionnaire was shared to collect socio-demographic and depression knowledge data as a pre-intervention method; content was then distributed to each group following a set schedule; the depression knowledge questionnaire was then administered to compare pre-intervention, post-intervention and follow-up literacy levels. Using the Scheffé and Least Significant Difference (LSD) multiple comparisons test, it was found that G1, which received the DEEP audiovisual intervention, differed significantly from the other groups, with higher depression knowledge scores in post-intervention stages. The DEEP audiovisual intervention, compared to the other formats used (narrative text format; news format), proved to be an effective tool for increasing depression knowledge in university students. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Artificial Intelligence in Orthodontic Smart Application for Treatment Coaching and Its Impact on Clinical Performance of Patients Monitored with AI-TeleHealth System
Healthcare 2021, 9(12), 1695; https://doi.org/10.3390/healthcare9121695 - 07 Dec 2021
Cited by 12 | Viewed by 2785
Abstract
Background: Treatment of malocclusion with clear removable appliances like Invisalign® or Spark™, require considerable higher level of patient compliance when compared to conventional fixed braces. The clinical outcomes and treatment efficiency strongly depend on the patient’s discipline. Smart treatment coaching applications, like [...] Read more.
Background: Treatment of malocclusion with clear removable appliances like Invisalign® or Spark™, require considerable higher level of patient compliance when compared to conventional fixed braces. The clinical outcomes and treatment efficiency strongly depend on the patient’s discipline. Smart treatment coaching applications, like strojCHECK® are efficient for improving patient compliance. Purpose: To evaluate the impact of computerized personalized decision algorithms responding to observed and anticipated patient behavior implemented as an update of an existing clinical orthodontic application (app). Materials and Methods: Variables such as (1) patient app interaction, (2) patient app discipline and (3) clinical aligner tracking evaluated by artificial intelligence system (AI) system—Dental monitoring® were observed on the set of 86 patients. Two 60-day periods were evaluated; before and after the app was updated with decision tree processes. Results: All variables showed significant improvement after the update except for the manifestation of clinical non-tracking in men, evaluated by artificial intelligence from video scans. Conclusions: Implementation of application update including computerized decision processes can significantly enhance clinical performance of existing health care applications and improve patients’ compliance. Using the algorithm with decision tree architecture could create a baseline for further machine learning optimization. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Detecting a Stroke-Affected Region in the Brain by Scanning with Low-Intensity Electromagnetic Waves in the Radio Frequency/Microwave Band
Healthcare 2021, 9(9), 1170; https://doi.org/10.3390/healthcare9091170 - 06 Sep 2021
Cited by 1 | Viewed by 1048
Abstract
There is a compelling need for a new form of head scanner to diagnose whether a patient is experiencing a stroke. Crucially, the scanner must be quickly and safely deployable at the site of the emergency to reduce the time between a diagnosis [...] Read more.
There is a compelling need for a new form of head scanner to diagnose whether a patient is experiencing a stroke. Crucially, the scanner must be quickly and safely deployable at the site of the emergency to reduce the time between a diagnosis and treatment being commenced. That will help to improve the long-term outlook for many patients, which in turn will help to reduce the high cost of stroke to national economies. This paper describes a novel scanning method that utilises low-intensity electromagnetic waves in the radio frequency/microwave band to detect a stroke-affected region in the brain. This method has the potential to be low cost, portable, and widely deployable, and it is intrinsically safe for the patient and operator. It requires no specialist shielding or power supplies and, hence, can be rapidly deployed at the site of the emergency. That could be at the patient’s bedside within a hospital, at the patient’s home or place of work, or in a community setting such as a GP surgery or a nursing home. Results are presented from an extensive programme of scans of inanimate test subjects that are materially valid representations of a human head. These results confirm that the scanning method is indeed capable of detecting a stroke-affected region in these subjects. The significance of these results is discussed, as well as ways in which the efficacy of the scanning methodology could be further improved. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Development of a System for Storing and Executing Bio-Signal Analysis Algorithms Developed in Different Languages
Healthcare 2021, 9(8), 1016; https://doi.org/10.3390/healthcare9081016 - 07 Aug 2021
Cited by 1 | Viewed by 995
Abstract
With the development of mobile and wearable devices with biosensors, various healthcare services in our life have been recently introduced. A significant issue that arises supports the smart interface among bio-signals developed by different vendors and different languages. Despite its importance for convenient [...] Read more.
With the development of mobile and wearable devices with biosensors, various healthcare services in our life have been recently introduced. A significant issue that arises supports the smart interface among bio-signals developed by different vendors and different languages. Despite its importance for convenient and effective development, however, it has been nearly unexplored. This paper focuses on the smart interface format among bio-signal data processing and mining algorithms implemented by different languages. We designed and implemented an advanced software structure where analysis algorithms implemented by different languages and tools would seem to work in one common environment, overcoming different developing language barriers. By presenting our design in this paper, we hope there will be much more chances for higher service-oriented developments utilizing bio-signals in the future. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Comparison of Intaglio Surface Trueness of Interim Dental Crowns Fabricated with SLA 3D Printing, DLP 3D Printing, and Milling Technologies
Healthcare 2021, 9(8), 983; https://doi.org/10.3390/healthcare9080983 - 03 Aug 2021
Cited by 10 | Viewed by 2259
Abstract
This study aimed to evaluate the intaglio surface trueness of interim dental crowns fabricated with three 3-dimensional (3D) printing and milling technologies. Dental crown was designated and assigned as a computer-aided design (CAD) reference model (CRM). Interim dental crowns were fabricated based on [...] Read more.
This study aimed to evaluate the intaglio surface trueness of interim dental crowns fabricated with three 3-dimensional (3D) printing and milling technologies. Dental crown was designated and assigned as a computer-aided design (CAD) reference model (CRM). Interim dental crowns were fabricated based on CRM using two types of 3D printer technologies (stereolithography apparatus and digital light processing) and one type of milling machine (n = 15 per technology). The fabricated interim dental crowns were obtained via 3D modeling of the intaglio surface using a laboratory scanner and designated as CAD test models (CTMs). The alignment and 3D comparison of CRM and CTM were performed based on the intaglio surface using a 3D inspection software program (Geomagic Control X). Statistical analysis was validated using one-way analysis of variance and Tukey HSD test (α = 0.05). There were significant differences in intaglio surface trueness between the three different fabrication technologies, and high trueness values were observed in the milling group (p < 0.05). In the milling group, there was a significant difference in trueness according to the location of the intaglio surface (p < 0.001). In the manufacturing process of interim dental crowns, 3D printing technologies showed superior and uniform manufacturing accuracy than milling technology. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
Telemedicine in the Time of the COVID-19 Pandemic: Results from the First Survey among Italian Pediatric Diabetes Centers
Healthcare 2021, 9(7), 815; https://doi.org/10.3390/healthcare9070815 - 28 Jun 2021
Cited by 9 | Viewed by 1760
Abstract
Background: Use of telemedicine for children and adolescents with type 1 diabetes at the beginning of the COVID-19 pandemic was investigated. Method: 68 Italian pediatric diabetes centers were invited to complete a survey about telemedicine usage in their pediatric patients, allocated to the [...] Read more.
Background: Use of telemedicine for children and adolescents with type 1 diabetes at the beginning of the COVID-19 pandemic was investigated. Method: 68 Italian pediatric diabetes centers were invited to complete a survey about telemedicine usage in their pediatric patients, allocated to the no-tech group (multiple daily injections and self-monitoring blood glucose) and the tech group (insulin pump and/or flash- or continuous-glucose monitoring). Results: 60.3% of the centers completed the survey. In both the no-tech and tech groups, the most used ways of communication were generic download portals, instant messaging with personal physicians’ mobiles, working emails, and phone calls to physicians’ mobiles, with no difference, except for the use of email being higher in the no-tech group (p = 0.03). Seventy-four percent of the centers did not have any systematization and/or reimbursement, with significant differences among regions (p = 0.03). Conclusions: Almost all Italian pediatric diabetes centers use telemedicine in a semi-volunteering manner, lacking proper codification, reimbursement system, legal traceability, and accreditation system. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
Article
The Impact of Health Information Sharing on Hospital Costs
Healthcare 2021, 9(7), 806; https://doi.org/10.3390/healthcare9070806 - 26 Jun 2021
Viewed by 1023
Abstract
Despite substantial progress in the adoption of health information technology (IT), researchers remain uncertain as to whether IT investments benefit hospitals. This study evaluates the effect of health information sharing on the cost of care, and whether the effect varies with context. Our [...] Read more.
Despite substantial progress in the adoption of health information technology (IT), researchers remain uncertain as to whether IT investments benefit hospitals. This study evaluates the effect of health information sharing on the cost of care, and whether the effect varies with context. Our results suggest that information sharing using health IT, specifically the extent (breadth) and level of detail (depth) of information sharing, helps to reduce the cost of care at the hospital level. The results also show that the effects of depth of information sharing on cost savings are salient in poor and less-concentrated regions, but not in wealthier, more-concentrated areas, whereas the the effects of breadth of information sharing on cost savings are equivalent across wealth and concentration. To realize the benefits of using health IT more effectively, policy makers’ strategies for encouraging active use of health IT should be informed by market characteristics. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
Article
The Accuracy of On-Call CT Reporting in Teleradiology Networks in Comparison to In-House Reporting
Healthcare 2021, 9(4), 405; https://doi.org/10.3390/healthcare9040405 - 01 Apr 2021
Viewed by 1087
Abstract
(1) Background: We aimed to compare the accuracy of after-hours CT reports created in a traditional in-house setting versus a teleradiology setting by assessing the discrepancy rates between preliminary and final reports. (2) Methods: We conducted a prospective study to determine the number [...] Read more.
(1) Background: We aimed to compare the accuracy of after-hours CT reports created in a traditional in-house setting versus a teleradiology setting by assessing the discrepancy rates between preliminary and final reports. (2) Methods: We conducted a prospective study to determine the number and severity of discrepancies between preliminary and final reports for 7761 consecutive after-hours CT scans collected over a 21-month period. CT exams were performed during on-call hours and were proofread by an attending the next day. Discrepancies between preliminary and gold-standard reports were evaluated by two senior attending radiologists, and differences in rates were assessed for statistical significance. (3) Results: A total of 7209 reports were included in the analysis. Discrepancies occurred in 1215/7209 cases (17%). Among these, 433/7209 reports (6%) showed clinically important differences between the preliminary and final reports. A total of 335/5509 of them were in-house reports (6.1%), and 98/1700 were teleradiology reports (5.8%). The relative frequencies of report changes were not significantly higher in teleradiology. (4) Conclusions: The accuracy of teleradiology reports was not inferior to that of in-house reports, with very similar clinically important differences rates found in both reporting situations. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Article
A Study of eHealth from the Perspective of Social Sciences
Healthcare 2021, 9(2), 108; https://doi.org/10.3390/healthcare9020108 - 21 Jan 2021
Cited by 4 | Viewed by 1642
Abstract
The field of social sciences has become increasingly important in eHealth. Patients currently engage more proactively with health services. This means that eHealth is linked to many different areas of Social Sciences. The main purpose of this research is to analyze the state-of-the-art [...] Read more.
The field of social sciences has become increasingly important in eHealth. Patients currently engage more proactively with health services. This means that eHealth is linked to many different areas of Social Sciences. The main purpose of this research is to analyze the state-of-the-art research on eHealth from the perspective of social sciences. To this end, a bibliometric analysis was conducted using the Web of Science database. The main findings show the evolution of publications, the most influential countries, the most relevant journals and papers, and the importance of the different areas of knowledge. Although there are some studies on eHealth within social sciences, most of them focus on very specific aspects and do not develop a holistic analysis. Thus, this paper contributes to academia by analyzing the state-of-the-art of research, as well as identifying the most relevant trends and proposing future lines of research such as the potential of eHealth as a professional training instrument, development of predictive models in eHealth, analysis of the eHealth technology acceptance model (TAM), efficient integration of eHealth within public systems, efficient budget management, or improvement in the quality of service for patients. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Review

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Review
A Blockchain and Artificial Intelligence-Based, Patient-Centric Healthcare System for Combating the COVID-19 Pandemic: Opportunities and Applications
Healthcare 2021, 9(8), 1019; https://doi.org/10.3390/healthcare9081019 - 08 Aug 2021
Cited by 12 | Viewed by 7166
Abstract
The world is facing multiple healthcare challenges because of the emergence of the COVID-19 (coronavirus) pandemic. The pandemic has exposed the limitations of handling public healthcare emergencies using existing digital healthcare technologies. Thus, the COVID-19 situation has forced research institutes and countries to [...] Read more.
The world is facing multiple healthcare challenges because of the emergence of the COVID-19 (coronavirus) pandemic. The pandemic has exposed the limitations of handling public healthcare emergencies using existing digital healthcare technologies. Thus, the COVID-19 situation has forced research institutes and countries to rethink healthcare delivery solutions to ensure continuity of services while people stay at home and practice social distancing. Recently, several researchers have focused on disruptive technologies, such as blockchain and artificial intelligence (AI), to improve the digital healthcare workflow during COVID-19. Blockchain could combat pandemics by enabling decentralized healthcare data sharing, protecting users’ privacy, providing data empowerment, and ensuring reliable data management during outbreak tracking. In addition, AI provides intelligent computer-aided solutions by analyzing a patient’s medical images and symptoms caused by coronavirus for efficient treatments, future outbreak prediction, and drug manufacturing. Integrating both blockchain and AI could transform the existing healthcare ecosystem by democratizing and optimizing clinical workflows. In this article, we begin with an overview of digital healthcare services and problems that have arisen during the COVID-19 pandemic. Next, we conceptually propose a decentralized, patient-centric healthcare framework based on blockchain and AI to mitigate COVID-19 challenges. Then, we explore the significant applications of integrated blockchain and AI technologies to augment existing public healthcare strategies for tackling COVID-19. Finally, we highlight the challenges and implications for future research within a patient-centric paradigm. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Other

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Perspective
Sharing Biomedical Data: Strengthening AI Development in Healthcare
Healthcare 2021, 9(7), 827; https://doi.org/10.3390/healthcare9070827 - 30 Jun 2021
Cited by 3 | Viewed by 2333
Abstract
Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive datasets and computational resources to create automatic tools for complex tasks that, until now, have been performed by humans. Massive data is a fundamental aspect of the most powerful AI-based algorithms. However, for [...] Read more.
Artificial intelligence (AI)-based solutions have revolutionized our world, using extensive datasets and computational resources to create automatic tools for complex tasks that, until now, have been performed by humans. Massive data is a fundamental aspect of the most powerful AI-based algorithms. However, for AI-based healthcare solutions, there are several socioeconomic, technical/infrastructural, and most importantly, legal restrictions, which limit the large collection and access of biomedical data, especially medical imaging. To overcome this important limitation, several alternative solutions have been suggested, including transfer learning approaches, generation of artificial data, adoption of blockchain technology, and creation of an infrastructure composed of anonymous and abstract data. However, none of these strategies is currently able to completely solve this challenge. The need to build large datasets that can be used to develop healthcare solutions deserves special attention from the scientific community, clinicians, all the healthcare players, engineers, ethicists, legislators, and society in general. This paper offers an overview of the data limitation in medical predictive models; its impact on the development of healthcare solutions; benefits and barriers of sharing data; and finally, suggests future directions to overcome data limitations in the medical field and enable AI to enhance healthcare. This perspective is dedicated to the technical requirements of the learning models, and it explains the limitation that comes from poor and small datasets in the medical domain and the technical options that try or can solve the problem related to the lack of massive healthcare data. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Perspective
The Critical Factors Affecting the Deployment and Scaling of Healthcare AI: Viewpoint from an Experienced Medical Center
Healthcare 2021, 9(6), 685; https://doi.org/10.3390/healthcare9060685 - 07 Jun 2021
Cited by 3 | Viewed by 1505
Abstract
Healthcare Artificial Intelligence (AI) has the greatest opportunity for development. Since healthcare and technology are two of Taiwan’s most competitive industries, the development of healthcare AI is an excellent chance for Taiwan to improve its health-related services. From the perspective of economic development, [...] Read more.
Healthcare Artificial Intelligence (AI) has the greatest opportunity for development. Since healthcare and technology are two of Taiwan’s most competitive industries, the development of healthcare AI is an excellent chance for Taiwan to improve its health-related services. From the perspective of economic development, promoting healthcare AI must be a top priority. However, despite having many breakthroughs in research and pilot projects, healthcare AI is still considered rare and is broadly used in the healthcare setting. Based on a medical center in Taiwan that has introduced a variety of healthcare AI into practice, this study discussed and analyzed the issues and concerns in the development and scaling of medical AIs from the perspective of various stakeholders in the healthcare setting, including the government, healthcare institutions, users (healthcare workers), and AI providers. The present study also identified critical influential factors for the deployment and scaling of healthcare AI. It is hoped that this paper can serve as an important reference for the advancement of healthcare AI not only in Taiwan but also in other countries. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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Project Report
Project Report on Telemedicine: What We Learned about the Administration and Development of a Binational Digital Infrastructure Project
Healthcare 2021, 9(4), 400; https://doi.org/10.3390/healthcare9040400 - 01 Apr 2021
Cited by 7 | Viewed by 1755
Abstract
This article describes the development of a German–Polish cross-border telemedicine project. Funded by the European Union Interreg Program, a cooperation between several German and Polish hospitals was developed over the course of 16 years, starting in 2002. Subprojects, governance and outcomes are described, [...] Read more.
This article describes the development of a German–Polish cross-border telemedicine project. Funded by the European Union Interreg Program, a cooperation between several German and Polish hospitals was developed over the course of 16 years, starting in 2002. Subprojects, governance and outcomes are described, and facilitators and barriers are identified. These points are reviewed with regard to their influence on medical, technical, administrative and medico-legal realisation. Full article
(This article belongs to the Special Issue Digital Transformation in Healthcare)
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