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Applied Sciences
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Pattern Recognition and Medical Data Analytics in Telemedicine
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Pattern Recognition and Medical Data Analytics in Telemedicine

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 9836

Special Issue Editors

Dr. Rafal Doniec

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Guest Editor
Department of Biosensors and Processing of Biomedical Signals, Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland
Interests: pattern recognition; telemedicine; machine and deep learning; biomedical data analysis; medical data
Prof. Dr. Marcin Grzegorzek

E-Mail Website
Guest Editor
Institute of Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562 Lübeck, Germany
Interests: biomedical engineering; artificial intelligence; pattern recognition; machine vision; machine learning; medical sensor
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ewaryst Tkacz

E-Mail Website
Guest Editor
Department of Biosensors and Processing of Biomedical Signals, Faculty of Biomedical Engineering, Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland
Interests: bioinformatics; biosensors; biomedical signals processing; miomedical image processing medical technology and medical devices
Prof. Dr. Wojciech Glinkowski

E-Mail Website
Guest Editor
Center of Excellence "TeleOrto" for Telediagnostics and Treatment of Disorders and Injuries of the Locomotor System, Department of Medical Informatics and Telemedicine, Medical University of Warsaw, Warsaw, Poland
Interests: image analysis; outcome measures; PROMIS; survey; survey methodology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Telemedicine is a rapidly evolving healthcare delivery mechanism via hardware and/or software through which consultation, medical assistance, and information can be communicated over the computer networks. There are many definitions of “Telemedicine”—each specific to the primary target of interest. During the COVID-19 pandemic, the importance of telemedicine increased. The reasons for applying telemedicine include: Separation or necessity to maintain social distance and distance between persons and/or resources; Conscious and more and more common use of telecommunications technologies; Dissemination and availability of data from smart and wearable sensors; Development of computing infrastructure and improvements of machine learning algorithms with the full inclusion of Artificial Intelligence; Optimization of costs and resources in healthcare. Background: Telemedicine has been around since the late 1980s, however, in the last two years there has been a significant increase in considerations and research regarding telemedicine, along with the growing importance of the development of mobile application implementation and production technology of sensors monitoring medical quantities. In this Special Issue, we would like to attract innovative and original research papers describing the latest research in the field of medical-based, engineering-based behavior. We also present a Special Issue to all those who wish to present their work in the area of health market management related to the use of sensor-based telemetry systems, using a wide range of artificial intelligence methods, including pattern recognition and machine learning algorithms. Potential topics include, but are not limited to:

  • Artificial Intelligence;
  • Cybersecurity processing of medical data;
  • Medical Data Analytics;
  • Future of Medical Data Analytics, Pattern Recognition and Telemedicine;
  • Machine Learning, Deep learning in Telemedicine application;
  • Pattern Recognition;
  • Personalized healthcare;

Dr. Rafal Doniec
Prof. Dr. Marcin Grzegorzek
Prof. Dr. Ewaryst Tkacz
Prof. Dr. Wojciech Glinkowski
Guest Editors

Manuscript Submission Information

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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

  • Artificial Intelligence
  • medical data analytics
  • machine learning
  • deep learning
  • cybersecurity
  • eHealth
  • mHealth telerehabilitation
  • telediagnostics
  • patient-oriented outcomes, personalized healthcare, digital modeling

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Published Papers (3 papers)

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Research

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11 pages, 1230 KiB  
Article
Remote, Touchless Interaction with Medical Images and Telementoring in the Operating Room Using a Kinect-Based Application—A Usability Study
by Wojciech Michał Glinkowski, Tomasz Miścior and Robert Sitnik
Appl. Sci. 2023, 13(21), 11982; https://doi.org/10.3390/app132111982 - 2 Nov 2023
Cited by 1 | Viewed by 1374
Abstract
Innovative technologies can improve user usability and satisfaction in computer-based activities in the work environment, including surgeons working in the operating room (OR). A scrubbed surgeon must ask unscrubbed staff to retrieve medical images from a surgical PACS system on a monitor in [...] Read more.
Innovative technologies can improve user usability and satisfaction in computer-based activities in the work environment, including surgeons working in the operating room (OR). A scrubbed surgeon must ask unscrubbed staff to retrieve medical images from a surgical PACS system on a monitor in a hybrid operating room. The study aimed to check users’ usability and satisfaction with the designed and developed Ortho_Kinect_OR application, which enables contactless control of access to medical images during surgery. The application also facilitates access to telemedicine applications such as intraoperative telementoring during orthopedic procedures or tele-education. The application’s usability was tested by assigning standardized tasks to surgeons for PACS and teleconferencing in the operating room. Hand gestures were recognized and translated to function like mouse buttons. Field tests conducted among orthopedic surgeons showed high usability and user satisfaction. PACS access in the operating room did not distract the orthopedic surgeon during orthopedic surgery procedures. All surgeons completed the tests and tasks without any problems. OR field test results showed high agreement among users and were very satisfactory. Junior surgeons and residents pointed out that people with average computer knowledge could use the application. It has been shown that the contactless system designed and built based on the Kinect sensor available on the shelves meets the requirements of the operating room environment and is easy to use. Touchless controller technology provides the opportunity to increase the use of intraoperative imaging previews and improve the safety of surgical patients by improving sterility and reducing unnecessary staff in the operating room. Using the Ortho_Kinect_OR application and the Kinect sensor, it is possible to provide contactless access to videoconference telementoring and PACS in the operating room without an orthopedic surgeon’s unnecessary distraction in the operating room environment. Full article
(This article belongs to the Special Issue Pattern Recognition and Medical Data Analytics in Telemedicine)
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18 pages, 5579 KiB  
Article
Explainable Artificial Intelligence Enabled TeleOphthalmology for Diabetic Retinopathy Grading and Classification
by Marwa Obayya, Nadhem Nemri, Mohamed K. Nour, Mesfer Al Duhayyim, Heba Mohsen, Mohammed Rizwanullah, Abu Sarwar Zamani and Abdelwahed Motwakel
Appl. Sci. 2022, 12(17), 8749; https://doi.org/10.3390/app12178749 - 31 Aug 2022
Cited by 16 | Viewed by 2496
Abstract
Recently, Telehealth connects patients to vital healthcare services via remote monitoring, wireless communications, videoconferencing, and electronic consults. By increasing access to specialists and physicians, telehealth assists in ensuring patients receive the proper care at the right time and right place. Teleophthalmology is a [...] Read more.
Recently, Telehealth connects patients to vital healthcare services via remote monitoring, wireless communications, videoconferencing, and electronic consults. By increasing access to specialists and physicians, telehealth assists in ensuring patients receive the proper care at the right time and right place. Teleophthalmology is a study of telemedicine that provides services for eye care using digital medical equipment and telecommunication technologies. Multimedia computing with Explainable Artificial Intelligence (XAI) for telehealth has the potential to revolutionize various aspects of our society, but several technical challenges should be resolved before this potential can be realized. Advances in artificial intelligence methods and tools reduce waste and wait times, provide service efficiency and better insights, and increase speed, the level of accuracy, and productivity in medicine and telehealth. Therefore, this study develops an XAI-enabled teleophthalmology for diabetic retinopathy grading and classification (XAITO-DRGC) model. The proposed XAITO-DRGC model utilizes OphthoAI IoMT headsets to enable remote monitoring of diabetic retinopathy (DR) disease. To accomplish this, the XAITO-DRGC model applies median filtering (MF) and contrast enhancement as a pre-processing step. In addition, the XAITO-DRGC model applies U-Net-based image segmentation and SqueezeNet-based feature extractor. Moreover, Archimedes optimization algorithm (AOA) with a bidirectional gated recurrent convolutional unit (BGRCU) is exploited for DR detection and classification. The experimental validation of the XAITO-DRGC method can be tested using a benchmark dataset and the outcomes are assessed under distinct prospects. Extensive comparison studies stated the enhancements of the XAITO-DRGC model over recent approaches. Full article
(This article belongs to the Special Issue Pattern Recognition and Medical Data Analytics in Telemedicine)
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Review

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18 pages, 558 KiB  
Review
Experiences of the Telemedicine and eHealth Conferences in Poland—A Cross-National Overview of Progress in Telemedicine
by Rafał J. Doniec, Natalia J. Piaseczna, Karen A. Szymczyk, Barbara Jacennik, Szymon Sieciński, Katarzyna Mocny-Pachońska, Konrad Duraj, Tomasz Cedro, Ewaryst J. Tkacz and Wojciech M. Glinkowski
Appl. Sci. 2023, 13(1), 587; https://doi.org/10.3390/app13010587 - 31 Dec 2022
Cited by 3 | Viewed by 4386
Abstract
The progress in telemedicine can be observed globally and locally. Technological changes in telecommunications systems are intertwined with developments in telemedicine. The recent COVID-19 pandemic has expanded the potential of teleconsultations and telediagnosis solutions in all areas of medicine. This article presents: (1) [...] Read more.
The progress in telemedicine can be observed globally and locally. Technological changes in telecommunications systems are intertwined with developments in telemedicine. The recent COVID-19 pandemic has expanded the potential of teleconsultations and telediagnosis solutions in all areas of medicine. This article presents: (1) an overview of milestones in the development of telecommunications systems that allow progress in telemedicine and (2) an analysis of the experiences of the last seven conferences of telemedicine and eHealth in Poland. The telemedicine and eHealth conferences have grown steadily in Poland since their inception in the late 1990s. An exemplary conference program content was used to assess the scientific maturity of the conference, measured by the indices of research dissemination and the impact of publications. The overview presents progress in selected areas of telemedicine, looking at local developments and broader changes. The growing interest in telemedicine in the world’s medical sciences is demonstrated by visibility metrics in Google Scholar, Pubmed, Scopus and Web of Science. National scientific events are assumed to raise interest in the population and influence the creation of general policies. As seen in the example of Poland, the activity of the scientific community gathered around the Polish Telemedicine Society led to novel legal acts that allowed the general practice of telemedicine during the SARS-CoV-2 pandemic. Local scientific conferences focusing on telemedicine research can be a catalyst for changes in attitudes and regulations and the preparation of recommendations for the practice of telemedicine and electronic health. On the basis of the results of this study, it can be concluded that the progress in telemedicine cannot be analyzed in isolation from the ubiquitous developments in technology and telecommunications. More research is needed to assess the cumulative impact of long-standing scientific conferences in telemedicine, as exemplified by the telemedicine and eHealth conferences in Poland. Full article
(This article belongs to the Special Issue Pattern Recognition and Medical Data Analytics in Telemedicine)
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