Redirigiendo al acceso original de articulo en 21 segundos...
Inicio  /  Information  /  Vol: 14 Par: 10 (2023)  /  Artículo
ARTÍCULO
TITULO

Healthcare Trust Evolution with Explainable Artificial Intelligence: Bibliometric Analysis

Pummy Dhiman    
Anupam Bonkra    
Amandeep Kaur    
Yonis Gulzar    
Yasir Hamid    
Mohammad Shuaib Mir    
Arjumand Bano Soomro and Osman Elwasila    

Resumen

Recent developments in IoT, big data, fog and edge networks, and AI technologies have had a profound impact on a number of industries, including medical. The use of AI for therapeutic purposes has been hampered by its inexplicability. Explainable Artificial Intelligence (XAI), a revolutionary movement, has arisen to solve this constraint. By using decision-making and prediction outputs, XAI seeks to improve the explicability of standard AI models. In this study, we examined global developments in empirical XAI research in the medical field. The bibliometric analysis tools VOSviewer and Biblioshiny were used to examine 171 open access publications from the Scopus database (2019?2022). Our findings point to several prospects for growth in this area, notably in areas of medicine like diagnostic imaging. With 109 research articles using XAI for healthcare classification, prediction, and diagnosis, the USA leads the world in research output. With 88 citations, IEEE Access has the greatest number of publications of all the journals. Our extensive survey covers a range of XAI applications in healthcare, such as diagnosis, therapy, prevention, and palliation, and offers helpful insights for researchers who are interested in this field. This report provides a direction for future healthcare industry research endeavors.

 Artículos similares

       
 
Ismail Bile Hassan, Masrah Azrifah Azmi Murad, Ibrahim El-Shekeil and Jigang Liu    
This study validates and extends the latest unified theory of acceptance and use of technology (UTAUT2) with the privacy calculus model. To evaluate the adoption of healthcare and e-government applications, researchers have recommended?in previous litera... ver más
Revista: Informatics

 
Enayat Rajabi and Somayeh Kafaie    
Building trust and transparency in healthcare can be achieved using eXplainable Artificial Intelligence (XAI), as it facilitates the decision-making process for healthcare professionals. Knowledge graphs can be used in XAI for explainability by structuri... ver más
Revista: Information

 
V A. Belyi,P. V. Smirnova,A. V. Chugunov     Pág. 97 - 109
The article presents the results of a survey of residents of St. Petersburg to identify their opinion on the relevance of the services of the "smart city". The study was carried out in March 2020 using a questionnaire method using a sample representing t... ver más

 
Santiago Figueroa, Javier Añorga and Saioa Arrizabalaga    
The growing adoption of Radio-frequency Identification (RFID) systems, particularly in the healthcare field, demonstrates that RFID is a positive asset for healthcare institutions. RFID offers the ability to save organizations time and costs by enabling ... ver más
Revista: Computers

 
Bassam M Al-Mahadeen     Pág. pp. 47 - 52
Numerous studies have reported the rapid increase in the number of individuals who use smartphones. However, smartphones appear to be increasingly used by healthcare workers, particularly physicians and nurses. Therefore, this study aims to investigate t... ver más