Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks

Artificial Neural Network Model for Prediction of Childhood Allergic Asthma Using Single Nucleotide Polymorphism Data

rodbar dam slope stability analysis using neural networks

در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...

Association of Salivary sCD14 Concentration Levels with Early Childhood Caries

Background: Early childhood caries (ECC) is a severe type of dental caries affecting infants and pre-school children. Because of the infectious nature of the disease, the immunologic response by the host plays an essential role in its development. Objective: This study investigated the association between the presence of salivary sCD14 and ECC. Methods: This study was carried out on 40 healthy ...

Prediction of Gas Lift Parameters Using Artificial Neural Networks

Comparison of Salivary Secretory IgA in Caries-free Children and Children with Severe Early Childhood Caries

Background & Aims: Sever early childhood caries (SECC) is a multifactor common disease that unfortunately there have been a lot of unknown points about it. This study was performed to compare the levels of total S-IgA in children with and without SECC. Methods: In this cross-sectional study 44 children aged 6-24 months were divided into two groups of with SECC (n=20) and without SECC (n=24). Th...