543: Using artificial intelligence to predict spontaneous preterm delivery
نویسندگان
چکیده
منابع مشابه
Using emotional intelligence to predict job stress: Artificial neural network and regression models
Introduction: These days, there is a consensus that emotional intelligence plays an important role in the success of individuals in different areas of life. Persons with higher emotional intelligence had lower stress in dealing with demands and pressures in the workplace. The purpose of this study was to use artificial neural network to predict job stress and to compare the performance of this ...
متن کاملProteomic Analysis of Early Mid-Trimester Amniotic Fluid Does Not Predict Spontaneous Preterm Delivery
OBJECTIVE The aim of this study was to identify early proteomic biomarkers of spontaneous preterm delivery (PTD) in mid-trimester amniotic fluid from asymptomatic women. METHODS This is a case-cohort study. Amniotic fluid from mid-trimester genetic amniocentesis (14-19 weeks of gestation) was collected from 2008 to 2011. The analysis was conducted in 24 healthy women with subsequent spontaneo...
متن کاملUsing Artificial Intelligence to Identify State Secrets
Whether officials can be trusted to protect national security information has become a matter of great public controversy, reigniting a long-standing debate about the scope and nature of official secrecy. The declassification of millions of electronic records has made it possible to analyze these issues with greater rigor and precision. Using machine-learning methods, we examined nearly a milli...
متن کاملUsing Artificial Intelligence to Assist Psychological Testing
Balancing ecological validity and control in psychological testing is a challenge. We have explored the use of Interactive Virtual Environment Technology to create an environment for psychological testing. Specifically we have created a Cocktail Party World to provide experimental control in the study of the phenomena of ostracism in its various forms. To address ecological validity we have cre...
متن کاملUsing Artificial Intelligence Techniques to Predict the Behaviour of Masonry Panels
Laboratory experimental data is often erroneous. This error is more apparent in data obtained from testing of anisotropic composite materials such as masonry wall panels. In this paper data colleted from the laboratory tests of masonry panels is presented. Methodologies for reducing (correcting) error in laboratory tested data are discussed. The concept of stiffness/strength corrector to model ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Journal of Obstetrics and Gynecology
سال: 2020
ISSN: 0002-9378
DOI: 10.1016/j.ajog.2019.11.559