Sonographer interaction with artificial intelligence: collaboration or conflict?

T G Day^{1

2}, J Matthew², S Budd², J V Hajnal², J M Simpson^{1

2}, R Razavi^{1

2}, B Kainz^{2

3

4}

Affiliations

¹ Department of Congenital Cardiology, Evelina London Children's Healthcare, Guy's and St Thomas' NHS Foundation Trust, London, UK.
² Faculty of Life Sciences and Medicine, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
³ Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
⁴ Department of Computing, Faculty of Engineering, Imperial College London, London, UK.

Free article

T G Day et al. Ultrasound Obstet Gynecol. 2023 Aug.

Free article

. 2023 Aug;62(2):167-174.

doi: 10.1002/uog.26238.

T G Day^{1

2}, J Matthew², S Budd², J V Hajnal², J M Simpson^{1

2}, R Razavi^{1

2}, B Kainz^{2

3

4}

¹ Department of Congenital Cardiology, Evelina London Children's Healthcare, Guy's and St Thomas' NHS Foundation Trust, London, UK.
² Faculty of Life Sciences and Medicine, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
³ Department of Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.
⁴ Department of Computing, Faculty of Engineering, Imperial College London, London, UK.

No abstract available

References

1. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat Med 2019; 25: 44-56.
1. Lecun Y, Bengio Y, Hinton G. Deep learning. Nature 2015; 521: 436-444.
1. US Food and Drug Administration. Artificial intelligence and machine learning (AI/ML)-enabled medical devices. https://www.fda.gov/medical-devices/software-medical-device-samd/artific... [Accessed 16 December 2022].
1. Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, Mahendiran T, Moraes G, Shamdas M, Kern C, Ledsam JR, Schmid MK, Balaskas K, Topol EJ, Bachmann LM, Keane PA, Denniston AK. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. Lancet Digit Heal 2019; 1: e271-297.
1. Day TG, Kainz B, Hajnal J, Razavi R, Simpson JM. Artificial intelligence, fetal echocardiography, and congenital heart disease. Prenat Diagn 2021; 41: 733-742.