Deep Learning Algorithm-Based Ultrasound Image Information in Diagnosis and Treatment of Pernicious Placenta Previa

Abstract

This study was to explore the value of the deep dictionary learning algorithm in constructing a B ultrasound scoring system and exploring its application in the clinical diagnosis and treatment of pernicious placenta previa (PPP). 60 patients with PPP were divided into a low-risk group (severe, implantable) and high-risk group (adhesive, penetrating) according to their clinical characteristics, B ultrasound imaging characteristics, and postpartum pathological examination results. Under PPP ultrasonic image information using the deep learning algorithm, the B ultrasound image diagnostic scoring system was established to predict the depth of various types of placenta accreta. The results showed that the cut-off values of severe, implantable, adhesive, and penetrating types were <2.3, 2.3-6.5, 6.5-9, and ≥9 points, respectively; there were significant differences in the termination of pregnancy and neonatal birth weight between the two groups ( P < 0.05 ); the positive predictive value, negative predictive value, and false positive rate of ultrasound images based on the deep dictionary learning algorithm for PPP were 95.33%, 94.89%, and 3.56%, respectively. Thus, the ultrasound image diagnostic scoring system based on the deep learning algorithm has an important predictive role for PPP, which can provide a more targeted diagnosis and treatment plan for patients in clinical practice and improve the prediction and treatment efficiency.

Landscape Design of Rural Characteristic Towns Based on Big Data Technology

“…It can be seen from Table 1 that when the cloud point data continue to improve, the registration time of the deep learning algorithm method and the proposed method is constantly rising, and the time used by the deep learning algorithm method is higher than that of the proposed method, which proves the registration time of the proposed method [20][21][22][23][24][25]. e proposed method is more efficient methods than deep learning algorithms.…”

Value of early pregnancy ultrasound combined with ultrasound score in the evaluation of placenta accreta in scar uterus: A retrospective cohort study

“…Such as multidisciplinary collaborative management, reasonable selection of surgical methods, etc. [ 19 , 20 ] At the same time, Yang et al [ 21 ] pointed out that ultrasound examination can determine the BF status of the cavity BF in the placental parenchyma and the junction of uterine serosa and bladder; the ultrasound scoring system can confirm whether the subject has PA at the thinnest part of the uterine myometrium with the help of conventional ultrasound signs and other information. The combination of the two can realize complementary advantages and disadvantages and effectively improve the value of disease diagnosis and treatment evaluation.…”

“…The combination of the two can realize complementary advantages and disadvantages and effectively improve the value of disease diagnosis and treatment evaluation. Based on this, it is believed that in clinical practice, to avoid missed diagnosis or misdiagnosis to the greatest extent, conventional ultrasound and ultrasound scoring systems can be integrated to carry out inspection and evaluation for patients with early scar uterine PA. [19][20][21]…”

Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology

“…Further examples of adverse pregnancy events with an often disastrous maternal and fetal outcome are placental abruption and pernicious placenta previa. Yang et al, therefore, investigated the predictive role of a scoring system for the occurrence of pernicious placenta previa [121], while the research group of Asadpour et al reported a method for identifying placental abruption [122].…”