Abstract
Introduction
The use of artificial intelligence (AI) in radiology and radiotherapy has been met with both scepticism and excitement. However, clinical integration of AI is well underway. Awareness of the current level of radiographers’ knowledge, skills and confidence in AI is essential to identify any educational needs necessary for successful adoption in practice. The aim of this survey was to determine the level of knowledge, skills and confidence in AI within UK radiographers.
Methods
A survey was created on Qualtrics® and promoted via social media (Twitter® / LinkedIn®). This survey was based on a previous UK pilot survey and was open to all UK radiographers, including students and retired radiographers. Participants were recruited by snowball sampling. Information was gathered on demographic characteristics of participants and on knowledge, skills and confidence in AI. Insight into what the participants understand by the term ‘AI’ was gained by means of a free text response. Analysis was performed using SPSS and NVIVO.
Results
411 responses were collected (80% from diagnostic radiography and 20% from a radiotherapy background), representative of the workforce distribution in the UK. There is a lack of confidence in the use of AI terminology. 57% of diagnostic and 49% radiotherapy respondents do not feel trained to implement AI in the clinical setting. Furthermore 52% and 64% respectively said they have not developed any skill in AI whilst 62% and 55% respectively stated that there is not enough training for radiographers available.
Conclusion
Further training in AI is essential to equip the workforce.
The use of artificial intelligence (AI) in radiology and radiotherapy has been met with both scepticism and excitement. However, clinical integration of AI is well underway. Awareness of the current level of radiographers’ knowledge, skills and confidence in AI is essential to identify any educational needs necessary for successful adoption in practice. The aim of this survey was to determine the level of knowledge, skills and confidence in AI within UK radiographers.
Methods
A survey was created on Qualtrics® and promoted via social media (Twitter® / LinkedIn®). This survey was based on a previous UK pilot survey and was open to all UK radiographers, including students and retired radiographers. Participants were recruited by snowball sampling. Information was gathered on demographic characteristics of participants and on knowledge, skills and confidence in AI. Insight into what the participants understand by the term ‘AI’ was gained by means of a free text response. Analysis was performed using SPSS and NVIVO.
Results
411 responses were collected (80% from diagnostic radiography and 20% from a radiotherapy background), representative of the workforce distribution in the UK. There is a lack of confidence in the use of AI terminology. 57% of diagnostic and 49% radiotherapy respondents do not feel trained to implement AI in the clinical setting. Furthermore 52% and 64% respectively said they have not developed any skill in AI whilst 62% and 55% respectively stated that there is not enough training for radiographers available.
Conclusion
Further training in AI is essential to equip the workforce.
| Original language | English |
|---|---|
| Publication status | Published (in print/issue) - 21 Aug 2021 |
| Event | ISRRT 2021 - Dublin/online, Ireland Duration: 20 Aug 2021 → 22 Aug 2021 https://isrrtdublin2021.org/ |
Conference
| Conference | ISRRT 2021 |
|---|---|
| Country/Territory | Ireland |
| Period | 20/08/21 → 22/08/21 |
| Internet address |
Keywords
- Artifical intelligence
- radiology
- radiography
