Zhiwen Yang

Zhiwen Yang

I have a wide range of research interests, including machine learning, deep learning and their application to computational biology, with a focus on developing tools to solve real world problems.

Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning

Published in PLOS ONE (JCR Q1, IF: 3.7), 2024

Supervised by Prof. Jianfei Huang, this project applied machine learning techniques to biostatistics data.

Key contributions include:

  • Designed a hybrid model combining Random Forest and MLP to predict infant behavior using maternal psychological data, achieving an AUC value of 0.97 and improving the validation set performance by over 15%.
  • Applied the Fuzzy C-Means clustering algorithm to grade the infant sleep quality and developed a regression model to deeply explore the relationship between maternal anxiety and infants’ contradictory behaviors.

Recommended citation: Yang, Z., Guo, X., & Huang, J. (2024). "Modeling the relationship between maternal health and infant behavioral characteristics based on machine learning." PLOS ONE. 19(8), e0307332.
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