Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers’ perspectives

Authors: Antwi, W.K., Akudjedu, T.N. and Botwe, B.O.

Journal: Insights into Imaging

Volume: 12

Issue: 1

eISSN: 1869-4101

DOI: 10.1186/s13244-021-01028-z

Abstract:

Purpose: Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa. Methods: The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness. Results: A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident. Conclusion: Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended.

http://eprints.bournemouth.ac.uk/35656/

Source: Scopus

Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers’ perspectives.

Authors: Antwi, W.K., Akudjedu, T.N. and Botwe, B.O.

Journal: Insights Imaging

Volume: 12

eISSN: 1869-4101

DOI: 10.1186/s13244-021-01028-z

Abstract:

PURPOSE: Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa. METHODS: The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness. RESULTS: A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident. CONCLUSION: Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-021-01028-z.

http://eprints.bournemouth.ac.uk/35656/

Source: PubMed

Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers' perspectives

Authors: Antwi, W.K., Akudjedu, T.N. and Botwe, B.O.

Journal: INSIGHTS INTO IMAGING

Volume: 12

Issue: 1

ISSN: 1869-4101

DOI: 10.1186/s13244-021-01028-z

http://eprints.bournemouth.ac.uk/35656/

Source: Web of Science (Lite)

Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers’ perspectives

Authors: Antwi, W.K., Botwe, B.O. and Akudjedu, T.N.

Journal: Insights into Imaging

Publisher: Springer

ISSN: 1869-4101

Abstract:

Purpose Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa.

Methods The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness.

Results A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident.

Conclusion Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended.

http://eprints.bournemouth.ac.uk/35656/

Source: Manual

Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers' perspectives.

Authors: Antwi, W.K., Akudjedu, T.N. and Botwe, B.O.

Journal: Insights into imaging

Volume: 12

Pages: 80

eISSN: 1869-4101

ISSN: 1869-4101

DOI: 10.1186/s13244-021-01028-z

Abstract:

Purpose

Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa.

Methods

The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness.

Results

A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident.

Conclusion

Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended.

Supplementary information

The online version contains supplementary material available at 10.1186/s13244-021-01028-z.

http://eprints.bournemouth.ac.uk/35656/

Source: Europe PubMed Central

Artificial intelligence in medical imaging practice in Africa: a qualitative content analysis study of radiographers’ perspectives

Authors: Antwi, W.K., Botwe, B.O. and Akudjedu, T.N.

Journal: Insights into Imaging

Volume: 12

Issue: 1

ISSN: 1869-4101

Abstract:

Purpose Studies have documented the clinical potentials of artificial intelligence (AI) in medical imaging practice to improving patient care. This study aimed to qualitatively explore the perception of radiographers relating to the integration of AI in medical imaging practice in Africa. Methods The study employed a qualitative design using an open-ended online instrument administered between March and August 2020. Participants consisted of radiographers working within Africa during the time of the study. Data obtained were analysed using qualitative content analysis. Six themes of concerns were generated: expectant tool; career insecurity; cost of new technology, equipment preservation and data insecurity; service delivery quality; need for expanding AI awareness. Results A total of 475 valid responses were obtained. Participants demonstrated a positive outlook about AI in relation to clinical quality improvement, competent diagnosis, radiation dose reduction and improvement in research. They however expressed concerns relating to the implementation of this technology, including job security and loss of core professional radiographer skills and roles. In addition, concerns regarding AI equipment maintenance, lack of awareness about AI and education and training opportunities were evident. Conclusion Awareness of the importance of AI in medical imaging practice was acknowledged; however, concerns relating to job security, data protection must be given critical attention for successful implementation of these advanced technologies in medical imaging in Africa. Inclusion of AI modules in the training of future radiographers is highly recommended.

http://eprints.bournemouth.ac.uk/35656/

Source: BURO EPrints