AI and Innovations in Imaging is a key program topic for ISUOG2024.
AI is rapidly changing prenatal care. By identifying those at risk of disease, automating the detection of abnormalities during pregnancy, and by reducing training time to achieve competent ultrasound system use, AI enables a broader range of frontline health workers to integrate this technology into routine prenatal care, particularly benefiting countries with limited personnel and experience.
Real-time scan guidance provided by AI enhances operator efficiency, improves diagnostic accuracy, and enables more precise procedures. Device-based algorithms offer recommendations on probe positioning, imaging technique, and additional views or measurements, aiding less experienced physicians in obtaining and interpreting ultrasound images accurately.
This innovation has the potential to enhances women's health by improving the early detection and management of pregnancy-related complications, particularly in resource-constrained settings.
UOG August 2023 cover image
Image from UOG: Unleashing the AI revolution: exploring the capabilities and challenges of large language models and text-to-image AI programs
Revolutionising fetal imaging: AI-enhanced ultrasound imaging for fetal health
World Congress 2023 Plenary Lecture - Aris Papageorghiou (UK)
Is AI going to provide a solution for gynecological diagnosis? What is the current state of play?
ISUOG World Congress 2023 Workshop
Why is AI and innovations in imaging a key topic at ISUOG2024?
Congress scientific program sessions on this topic include:
Sunday 15 September
- AI is everywhere: separating hype from hope (13:40-14:50, Hall P1-2)
Monday 16 September
- Multiple applications of Artificial Intelligence (11:00-11:40, Hall P3)
- Novel AI for prediction of pregnancy outcomes (14:30-15:30, Hall P3)
Tuesday 17 September
- AI in gynecological ultrasound: becoming reality (08:30-09:10, Hall F1-3)
Recent UOG Articles
Validation of machine-learning model for first-trimester prediction of pre-eclampsia using cohort from PREVAL study - M. M. Gil, D. Cuenca-Gómez, V. Rolle, M. Pertegal, C. Díaz, R. Revello, B. Adiego, M. Mendoza, F. S. Molina, B. Santacruz, Z. Ansbacher-Feldman, H. Meiri, R. Martin-Alonso, Y. Louzoun, C. De Paco Matallana. First published: 12 September 2023
Performance of machine-learning approach for prediction of pre-eclampsia in a middle-income country - J. Torres-Torres, J. R. Villafan-Bernal, R. J. Martinez-Portilla, J. A. Hidalgo-Carrera, G. Estrada-Gutierrez, R. Adalid-Martinez-Cisneros, L. Rojas-Zepeda, S. Acevedo-Gallegos, D. M. Camarena-Cabrera, M. Y. Cruz-Martínez, S. Espino-y-Sosa. First published: 29 September 2023
Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance? - T. G. Day, J. Matthew, S. F. Budd, L. Venturini, R. Wright, A. Farruggia, T. V. Vigneswaran, V. Zidere, J. V. Hajnal, R. Razavi, J. M. Simpson, B. Kainz. First published: 10 January 2024
Role of AI-assisted automated cardiac biometrics in screening for fetal coarctation of aorta - C. A. Taksoee-Vester, K. Mikolaj, O. B. B. Petersen, N. G. Vejlstrup, A. N. Christensen, A. Feragen, M. Nielsen, M. B. S. Svendsen, M. G. Tolsgaard. First published: 09 February 2024
Impact of Medical Device Regulation on use of ultrasound-based prediction models in clinical practice - A. Kotlarz, W. Froyman, L. Valentin, A. Testa, M. Van Hove, B. Van Calster, T. Bourne, D. Timmerman. First published: 03 May 2024
- How are AI-assisted tools being used today?
- What is the future of Artificial Intelligence in medical Imaging?
- What barriers are there to revolutionizing the treatment of disease during pregnancy with Artificial intelligence?
- What are the benefits of machine-based learning when teaching obstetric imaging to medical trainees?