Javascript must be enabled to continue!
Current practical experience with artificial intelligence in clinical radiology: a survey of the European Society of Radiology
View through CrossRef
AbstractA survey among the members of European Society of Radiology (ESR) was conducted regarding the current practical clinical experience of radiologists with Artificial Intelligence (AI)-powered tools. 690 radiologists completed the survey. Among these were 276 radiologists from 229 institutions in 32 countries who had practical clinical experience with an AI-based algorithm and formed the basis of this study. The respondents with clinical AI experience included 143 radiologists (52%) from academic institutions, 102 radiologists (37%) from regional hospitals, and 31 radiologists (11%) from private practice. The use case scenarios of the AI algorithm were mainly related to diagnostic interpretation, image post-processing, and prioritisation of workflow. Technical difficulties with integration of AI-based tools into the workflow were experienced by only 49 respondents (17.8%). Of 185 radiologists who used AI-based algorithms for diagnostic purposes, 140 (75.7%) considered the results of the algorithms generally reliable. The use of a diagnostic algorithm was mentioned in the report by 64 respondents (34.6%) and disclosed to patients by 32 (17.3%). Only 42 (22.7%) experienced a significant reduction of their workload, whereas 129 (69.8%) found that there was no such effect. Of 111 respondents who used AI-based algorithms for clinical workflow prioritisation, 26 (23.4%) considered algorithms to be very helpful for reducing the workload of the medical staff whereas the others found them only moderately helpful (62.2%) or not helpful at all (14.4%). Only 92 (13.3%) of the total 690 respondents indicated that they had intentions to acquire AI tools. In summary, although the assistance of AI algorithms was found to be reliable for different use case scenarios, the majority of radiologists experienced no reduction of practical clinical workload.
Springer Science and Business Media LLC
Title: Current practical experience with artificial intelligence in clinical radiology: a survey of the European Society of Radiology
Description:
AbstractA survey among the members of European Society of Radiology (ESR) was conducted regarding the current practical clinical experience of radiologists with Artificial Intelligence (AI)-powered tools.
690 radiologists completed the survey.
Among these were 276 radiologists from 229 institutions in 32 countries who had practical clinical experience with an AI-based algorithm and formed the basis of this study.
The respondents with clinical AI experience included 143 radiologists (52%) from academic institutions, 102 radiologists (37%) from regional hospitals, and 31 radiologists (11%) from private practice.
The use case scenarios of the AI algorithm were mainly related to diagnostic interpretation, image post-processing, and prioritisation of workflow.
Technical difficulties with integration of AI-based tools into the workflow were experienced by only 49 respondents (17.
8%).
Of 185 radiologists who used AI-based algorithms for diagnostic purposes, 140 (75.
7%) considered the results of the algorithms generally reliable.
The use of a diagnostic algorithm was mentioned in the report by 64 respondents (34.
6%) and disclosed to patients by 32 (17.
3%).
Only 42 (22.
7%) experienced a significant reduction of their workload, whereas 129 (69.
8%) found that there was no such effect.
Of 111 respondents who used AI-based algorithms for clinical workflow prioritisation, 26 (23.
4%) considered algorithms to be very helpful for reducing the workload of the medical staff whereas the others found them only moderately helpful (62.
2%) or not helpful at all (14.
4%).
Only 92 (13.
3%) of the total 690 respondents indicated that they had intentions to acquire AI tools.
In summary, although the assistance of AI algorithms was found to be reliable for different use case scenarios, the majority of radiologists experienced no reduction of practical clinical workload.
Related Results
Henry Lives! Learning from Lawson Fandom
Henry Lives! Learning from Lawson Fandom
Since his death in 1922, Henry Lawson’s “spirit” has been kept alive by admirers across Australia. Over the last century, Lawson’s reputation in the academy has fluctuated yet fan ...
New Era’s of Artificial Intelligence in Pharmaceutical Industries
New Era’s of Artificial Intelligence in Pharmaceutical Industries
Artificial Intelligence (AI) is the future of pharmaceutical industries. We make our tasks easier with help of Artificial Intelligence in future. With help of Artificial Intelligen...
Clinical Reasoning and Artificial Intelligence
Clinical Reasoning and Artificial Intelligence
Context: Artificial intelligence refers to a set of systems that are capable of performing functions similar to human intelligent functions. Today, artificial intelligence has been...
Artificial intelligence in medicine: Current applications in cardiology, oncology, and radiology
Artificial intelligence in medicine: Current applications in cardiology, oncology, and radiology
In this article, artificial intelligence (AI) usage and its benefits in medicine are reviewed in the oncology, radiology, and cardiology fields. The relevant literature was searche...
“Artificial Intelligence”: The Associative Field of Journalism Students
“Artificial Intelligence”: The Associative Field of Journalism Students
Artificial Intelligence today can be called one of the most discussed phenomena. Meanwhile, the boundaries of this term are extremely broad and blurred. Such breadth of meaning may...
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE STANDARDIZATION AND IMPROVEMENT OF NURSING CARE
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE STANDARDIZATION AND IMPROVEMENT OF NURSING CARE
Background. The rapid advancement of artificial intelligence technologies and their implementation in medical practice create new opportunities for enhancing the quality of patient...
Artificial Intelligence and Justice: Opportunities and Risks
Artificial Intelligence and Justice: Opportunities and Risks
. The article focuses on the possibility of using artificial intelligence technology in judicial activity and assesses the admissibility of granting artificial intelligence the pow...
EFFECT OF ARTIFICIAL INTELLIGENCE ON ONE-TO-ONE EMOTIONAL REGULATION AND PSYCHOLOGICAL INTERVENTION SYSTEM OF MIDDLE SCHOOL STUDENTS
EFFECT OF ARTIFICIAL INTELLIGENCE ON ONE-TO-ONE EMOTIONAL REGULATION AND PSYCHOLOGICAL INTERVENTION SYSTEM OF MIDDLE SCHOOL STUDENTS
Abstract
Background
This study discusses the effectiveness of artificial intelligence in one-to-one psychological intervention s...

