| Autor: |
Lam‐Rachlin, J., Punn, R., Lachaud, M., David, N., Garmel, S., Bessis, R., Heiligenstein, M., Sylvester‐Armstrong, K.R., Kennedy, J.P., Rebarber, A., Fox, N., Chelli, D., Boukobza, P., Uzan, P., Vaksmann, G., Cohen, L., Levy, M., Stos, B., De Boisredon, M., Thorey, V. |
| Předmět: |
|
| Zdroj: |
Ultrasound in Obstetrics & Gynecology; Sep2024 Supplement 1, Vol. 64, p63-63, 1p |
| Abstrakt: |
This article discusses the use of artificial intelligence (AI) software to improve the detection of congenital heart disease (CHD) during second trimester ultrasounds. The software analyzes ultrasound video clips to identify morphological abnormalities associated with CHD. The study found that the AI software improved the accuracy of detection for these abnormalities when used by obstetrics and gynecology (OBGYN) and maternal fetal medicine (MFM) professionals. The software also reduced analysis time compared to manual review. This research suggests that AI technology can enhance the detection of CHD during prenatal ultrasounds. [Extracted from the article] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
Plný text