This webinar introduced healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...

1 School of Public Health, Xinjiang Medical University, Urumqi, China 2 The Second Affiliated Hospital of Xi’an Jiaotong University Xinjiang Hospital, People’s Hospital of Xinjiang Uygur Autonomous ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Objective: Based on the Bayesian network, this study investigates the impact pathways of multidimensional factors related to the living environment—specifically housing factors, exposure to daily ...

Cross-sectional network analysis was employed to explore the complex relationships between depression, anxiety, insomnia, somatic symptoms, childhood trauma, self-esteem, social support, and emotional ...

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...

Abstract: Bayesian network is a graphical model based on probabilities to represent and inference in uncertain conditions. In the field of Bayesian network, structure learning from data is an ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Abstract: With the objective of enhancing the information security of traditional communication networks, an information security system based on an improved Bayesian network model was designed within ...