Environmental Factor

Environmental factors are increasingly recognized as significant influences on various health outcomes and technological applications. Current research focuses on leveraging machine learning, particularly neural networks (like ResNet and DeiT) and statistical models (including Random Forest, Logistic Regression, and LSTM), to predict and understand these influences across diverse areas, such as disease progression (e.g., multiple sclerosis, breast cancer, depression), building energy consumption, and wildfire risk assessment. These studies highlight the potential for improved prediction and resource allocation through data-driven approaches, offering valuable insights for both public health and environmental management.