Background: The ultrasound scan represents the first tool that obstetricians use in fetal evaluation, but sometimes, it can be limited by mobility or fetal position, excessive thickness of the maternal abdominal wall, or the presence of post-surgical scars on the maternal abdominal wall. Artificial intelligence (AI) has already been effectively used to measure biometric parameters, automatically recognize standard planes of fetal ultrasound evaluation, and for disease diagnosis, which helps conventional imaging methods. The usage of information, ultrasound scan images, and a machine learning program create an algorithm capable of assisting healthcare providers by reducing the workload, reducing the duration of the examination, and increasing the correct diagnosis capability. The recent remarkable expansion in the use of electronic medical records and diagnostic imaging coincides with the enormous success of machine learning algorithms in image identification tasks. Objectives: We aim to review the most relevant studies based on deep learning in ultrasound anomaly scan evaluation of the most complex fetal systems (heart and brain), which enclose the most frequent anomalies.

Background. Hospitalizations for non-COVID-19 ailments have drastically decreased during the SARS-CoV-2 pandemic. This study sought to assess the pattern of obstetrical hospitalizations versus patients who go to the medical unit for gynecological conditions during and following the COVID-19 pandemic. Methodology. In order to find all obstetrical and gynecological patients who were admitted to the Emergency County Clinical Hospital Craiova, Romania, during the pre-pandemic period (March-December 2019), during the pandemic (March-December 2020 and March-December 2021), and after the pandemic (March-December 2022), we used an electronic database for this study. Results. Related to obstetrical conditions, including childbirth, a substantial increase in hospitalizations during the pandemic (2020) can be highlighted compared to the previous year. Contrary to the increase in the number of obstetric patients, a drastic decrease can be observed in the number of gynecological patients, a decrease that is maintained throughout the years. Conclusions. Hospitalizations for obstetrical and gynecological diseases fell sharply during the COVID-19 pandemic and have not yet returned to their pre-pandemic levels.