1,721,159 research outputs found
The Internet of Medical Things:Opportunities, Benefits, Challenges and Concerns
Full text linkIn this narrative review, we investigate the potential opportunities and benefits, as well as the challenges and concerns of integrating the Internet of Things in healthcare. The opportunities include enhanced patient monitoring and management, improved efficiency and resource utilization, personalized and precision medicine, empowering patients and promoting self-management, and data-driven decision-making, while the challenges include security and privacy risks, interoperability and integration, regulatory and compliance issues, ethical considerations and impact on healthcare professionals and patients. These challenges must be carefully weighed against the benefits before deployment of the IoMT-enabled services.</p
Towards a Consistent Representation of Contradictions Within Health Data for Efficient Implementation of Data Quality Assessments
No full textMobile health applications for travellers
No full textThe number of travellers is increasing every day. Nowadays, disease outbreaks, natural disasters, migrations and other dangerous situations may take place all over the world putting travellers’ health at risk. Therefore, travellers should have the ability to be kept informed for health care issues during their trips. On the other hand, the evolution of the technology has offered a lot of solutions in many aspects of the human’s everyday life. The "smart" mobile devices which are used daily can provide many useful applications to improve the quality of human health.The aim of the current PhD Thesis is to investigate the travellers’ perceptions about m-Health (mobile health) applications through the development and the assessment of a pilot mobile application which informs travellers about health issues. At the same time, in the current Thesis the effectiveness of a proposed theoretical evaluation model for health related applications was tested.On this Doctoral Thesis, a literature review was conducted in order to record the current technological status of the mobile health applications available for travellers. Also, two empirical studies took place in order to measure travellers’ perception about the above technology. On the first survey, a new theoretical model which assesses technological ideas was used. The proposed theoretical model was found to provide positive results on travellers’ perceptions about mobile health applications. In addition, a pilot mobile application was developed to inform travellers for health care issues automatically depending on their current location. The pilot application was named "SMART Travel Health" and it was developed based on the positive findings of the aforementioned survey. An empirical evaluation of this pilot application was conducted by a second survey. The results revealed that users have a positive attitude towards this technology and they accept it, regardless of their personal characteristics. The acceptance of these technologies by the travellers was also confirmed by the relevant scientific literature. For both of the surveys the data analysis was performed using the Partial Least Squares Path Modeling (PLS-PM) – Structural Equation Modeling (SEM) statistical techniques. Further evaluation of the proposed theoretical model for the assessment of technological ideas would be useful in the future to prove the reliability of this method. Also, future work on this field of study could include further assessment of the mobile applications technology for travellers related to health care issues.Δεδομένου ότι ο αριθμός των ταξιδιωτών συνεχώς αυξάνεται και ότι ανά πάσα στιγμή, σε οποιοδήποτε μέρος του πλανήτη, μπορεί να εμφανιστούν εξάρσεις επιδημιών, φυσικές καταστροφές, μεταναστεύσεις πληθυσμών και άλλες παρόμοιες καταστάσεις που μπορούν να θέσουν σε κίνδυνο την υγεία των ταξιδιωτών, θα πρέπει να υπάρχει η δυνατότητα έγκαιρης και έγκυρης ενημέρωσης όσων ταξιδεύουν. Από τη άλλη πλευρά, η εξέλιξη της τεχνολογίας προσφέρει τεχνολογικές λύσεις σε πολλούς τομείς της καθημερινότητας. Ειδικότερα, οι «έξυπνες» κινητές συσκευές χρησιμοποιούνται πλέον ευρέως παρέχοντας πολλές εφαρμογές για την βελτίωση της ποιότητας της ζωής του ανθρώπου. Ο σκοπός της παρούσας Διδακτορικής Διατριβής είναι η διερεύνηση της άποψης των ταξιδιωτών για τις εφαρμογές Κινητής Υγείας μέσω της αξιολόγησης μίας πιλοτικής εφαρμογής που λειτουργεί σε «έξυπνες» κινητές συσκευές και ενημερώνει τους ταξιδιώτες για θέματα υγείας. Επιπροσθέτως, στην παρούσα Διατριβή διερευνάται η αποτελεσματικότητα ενός προτεινόμενου θεωρητικού μοντέλου αξιολόγησης τεχνολογικών ιδεών για εφαρμογές που σχετίζονται με θέματα υγείας. Στην παρούσα Διδακτορική Διατριβή έγινε μία βιβλιογραφική ανασκόπηση για την καταγραφή της υπάρχουσας τεχνολογικής κατάστασης στον τομέα της Κινητής Υγείας των ταξιδιωτών. Επίσης, διεξήχθησαν δύο εμπειρικές μελέτες με στόχο την καταγραφή της άποψης των ταξιδιωτών για την παραπάνω τεχνολογία. Στην πρώτη μελέτη δομήθηκε και εφαρμόστηκε ένα νέο θεωρητικό μοντέλο διερεύνησης τεχνολογικών ιδεών. Το προτεινόμενο εργαλείο αξιολόγησης βρέθηκε να παρέχει θετικά αποτελέσματα σχετικά με τις απόψεις των ταξιδιωτών για τις κινητές εφαρμογές στον χώρο της υγείας. Επίσης, αναπτύχτηκε η πιλοτική εφαρμογή “SMART Travel Health” η οποία ενημερώνει αυτόματα τους ταξιδιώτες με βάση την γεωγραφική τους θέση για θέματα υγείας και λειτουργεί σε «έξυπνες» κινητές συσκευές. Η πιλοτική εφαρμογή, βασίστηκε στην θετική στάση των ταξιδιωτών για μία τέτοιου είδους τεχνολογία. Στην δεύτερη μελέτη, αξιολογήθηκε η πιλοτική εφαρμογή και βρέθηκε ότι οι χρήστες της αποδέχονται την συγκεκριμένη τεχνολογία και έχουν θετική άποψη για αυτή, ανεξάρτητα από τα προσωπικά χαρακτηριστικά τους. Η αποδοχή παρόμοιων τεχνολογιών από τους ταξιδιώτες επιβεβαιώνεται και από την διεθνή επιστημονική βιβλιογραφία. Η ανάλυση των δεδομένων και για τις δύο εμπειρικές μελέτες βασίστηκε στην στατιστική μέθοδο των Partial Least Squares Path Modeling (PLS–PM) – Μοντέλα Δομικών Εξισώσεων (SEM). Η επανεξέταση της λειτουργίας του προτεινόμενου θεωρητικού μοντέλου αξιολόγησης τεχνολογικής ιδέας, θα ήταν χρήσιμη στο μέλλον για τον έλεγχο της αξιοπιστίας της συγκεκριμένης μεθόδου. Ακόμα, μελλοντικές εργασίες σε αυτό το ερευνητικό πεδίο θα μπορούσαν να περιλαμβάνουν περαιτέρω αξιολόγηση της τεχνολογίας των κινητών εφαρμογών για θέματα υγείας που απευθύνονται σε ταξιδιώτες
Travelers' Perceptions about m-Health Technology
No full textThe aim of this paper is to present the perceptions of the Travelers about the m-Health Technology. An empirical study was conducted to record travelers’ mobile technology usage behavior and their perceptions about a proposed idea for an m-Health application. A pilot mobile application which informs travelers for health issues automatically, according to their current location was developed based on the finding of the study and evaluated by a small group of users. Based on the study findings, over 84% of the Greek Travelers were using Smartphones, but only 27.6% had used an m-Health application. Additionally, they expressed their positive attitude about the idea for a “Smart” mobile application. After a quantitative and qualitative evaluation, the pilot mobile application found to be accepted by the travelers who state their intention to use this technology on the future. Overall, it can be assumed that Greek Travelers have a good view about m-Health Technologies
A Novel Blockchain-Based Model for Secure Genomic Data Management
Full text linkAdvancements in personalized medicine require secure, transparent, and privacy-preserving genomic data management systems. This study proposes a novel hybrid blockchain-based genomic data model integrating Self-Sovereign Identity (SSI), Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and decentralized storage Interplanetary File System (IPFS) to enable secure, privacy-compliant, patient-controlled genomic data exchange. The model leverages Polygon Proof-of-Stake (PoS) blockchain by deploying a smart contract that enforces fully access control functions applied on 100 samples of synthetic genomic data, ensuring only authorized researchers with valid DIDs and VCs can retrieve genomic data. Later, we performed five tests to evaluate our model performance. Security evaluations confirmed 100% data integrity validation through SHA-256 hash validation on-chain, ensuring tamper-proof genomic data storage. Unauthorized access attempts resulted in zero successful breaches, demonstrating the robustness of SSI-based authentication by showing revoked access. Additionally, IPFS data availability testing confirmed reliable and decentralized data retrieval through the Content Identifier (CID) on-chain. The model's access revocation mechanism enabled real-time patient control over genomic data access, ensuring compliance with GDPR privacy regulations. The proposed model provides a scalable, secure, and privacy-compliant solution for genomic data sharing in precision medicine, empowering patients with full control over their genetic data while facilitating researchers to trustworthy, decentralized data useability for precision research.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Enhancing Diagnostic Precision:Utilising a Large Language Model to Extract U Scores from Thyroid Sonography Reports
Full text linkThis study evaluates the performance of ChatGPT-4, a Large Language Model (LLM), in automatically extracting U scores from free-text thyroid ultrasound reports collected from University Hospitals Birmingham (UHB), UK, between 2014 and 2024. The LLM was provided with guidelines on the U classification system and extracted U scores independently from 14,248 de-identified reports, without access to human-assigned scores. The LLM-extracted scores were compared to initial clinician-assigned and refined U scores provided by expert reviewers. The LLM achieved 97.7% agreement with refined human U scores, successfully identifying the highest U score in 98.1% of reports with multiple nodules. Most discrepancies (2.5%) were linked to ambiguous descriptions, multi-nodule reports, and cases with human-documented uncertainty. While the results demonstrate the potential for LLMs to improve reporting consistency and reduce manual workload, ethical and governance challenges such as transparency, privacy, and bias must be addressed before routine clinical deployment. Embedding LLMs into reporting workflows, such as Online Analytical Processing (OLAP) tools, could further enhance reporting quality and consistency.</p
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