OBJECTIVE: Deep vein thrombosis (DVT) is a disease caused by abnormal blood clots in deep veins. Accurate segmentation of DVT is important to facilitate the diagnosis and treatment. In the current study, we proposed a fully automatic method of DVT de...
Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referre...
BACKGROUND: The aim of this study was to develop a diagnostic prediction model to improve identification of acute symptomatic portal vein thrombosis (PVT).
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
32725833
To date, coronavirus disease 2019 (COVID-19) has infected millions of people worldwide. Ultrasound plays an indispensable role in the diagnosis, monitoring, and follow-up of patients with COVID-19. In this study, we used a robotic tele-echography sys...
The objective is to explore the application effect of comprehensive nursing intervention in prevention of lower extremity deep vein thrombosis and pulmonary embolism in urological patients undergoing laparoscopic and robot-assisted laparoscopic surge...
Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
33928796
In order to overcome the shortage of the current costly DVT diagnosis and reduce the waste of valuable healthcare resources, we proposed a new diagnostic approach based on machine learning pre-test prediction models using EHRs. We examined the sociod...
Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
33625875
Deep venous thrombosis (DVT) is associated with significant morbidity, mortality, and increased healthcare costs. Standard scoring systems for DVT risk stratification often provide insufficient stratification of hospitalized patients and are unable t...
A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been reached regarding the optimal model. New approaches such as machine learning (ML) strategies are po...
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.