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Digital Innovations in Healthcare

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

Deadline for manuscript submissions: 30 May 2025 | Viewed by 272

Special Issue Editors


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Guest Editor
Department of Computer Science and Information Engineering, Fu Jen Catholic University, Taipei, Taiwan
Interests: data mining; knowledge engineering; machine learning; medical informatics; multimedia database; music informatics

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Guest Editor
Institute of Systems and Robotics (ISR-UC), and Department of Electrical and Computer Engineering (DEEC-UC), University of Coimbra, Pólo II, PT-3030-290 Coimbra, Portugal
Interests: computational intelligence; intelligent control; computational learning; machine learning; fuzzy systems; neural networks; optimization; modeling; simulation; estimation; prediction; control; big data; robotics; mobile robotics and intelligent vehicles; robot manipulators control; sensing; soft sensors; automation; industrial systems; embedded systems; real-time systems; general architectures and systems for controlling robot manipulators; mobile robots
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue will explore the cutting-edge digital innovations that are transforming the healthcare sector. We invite research that focuses on the development and application of AI and machine learning in healthcare, particularly in enhancing diagnostic accuracy, optimizing patient care, and improving healthcare management systems. Key areas of interest include, but are not limited to, the following: 

  • AI-driven healthcare systems for patient care and operational efficiency;
  • machine learning models for disease diagnosis and outcome prediction;
  • natural language processing (NLP) in medical records analysis;
  • multimodal data fusion for improved healthcare decision-making;
  • real-time monitoring and digital diagnostics in healthcare.

Prof. Dr. Jia-Lien Hsu
Dr. Rui Araújo
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 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

  • healthcare AI
  • machine learning
  • disease diagnosis
  • medical NLP
  • digital health solutions

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Published Papers (1 paper)

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Research

15 pages, 1958 KiB  
Article
XClinic Sensors: Validating Accuracy in Measuring Range of Motion Across Trauma Conditions
by Ilaria Ruotolo, Giovanni Sellitto, Giovanni Galeoto, Donatella Valente, Emanuele Amadio, Anna Berardi, Francescaroberta Panuccio, Raffaele La Russa, Umberto Guidoni, Gianpietro Volonnino and Paola Frati
Appl. Sci. 2025, 15(9), 4731; https://doi.org/10.3390/app15094731 - 24 Apr 2025
Abstract
Background: Accidents and injuries are major causes of chronic disability, leading to a loss of healthy years. Accurate assessment is essential for planning personalized rehabilitation programs. In recent years, wearable sensors have been introduced into research for motion analysis. This study aimed to [...] Read more.
Background: Accidents and injuries are major causes of chronic disability, leading to a loss of healthy years. Accurate assessment is essential for planning personalized rehabilitation programs. In recent years, wearable sensors have been introduced into research for motion analysis. This study aimed to validate the Xclinic wearable sensors for ROM assessment in patients with trauma. Methods: Participants were recruited from the Sapienza University of Rome (September 2023–November 2024) after road accident trauma. The active ROM of the hip, knee, and ankle was assessed bilaterally based on the injury. The SF-36 and other specific tools were also administered. Construct validity was tested using Pearson’s correlation coefficient. Results: A total of 44 participants (mean age 42.7 ± 17.3 years, 69% male) were included. Item-by-item analysis revealed significant correlations, with notable findings related to other outcome measures. Conclusions: The correlation between joint restrictions, functional impairment, and psychosocial factors highlights the need to integrate physical and psychological care into rehabilitation. Further research is needed to refine assessment tools to improve patients’ quality of life. Full article
(This article belongs to the Special Issue Digital Innovations in Healthcare)
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