Global biodiversity is rapidly declining, yet we still do not fully understand the relationships between biodiversity and human health and well-being. As debated, the loss of biodiversity or reduced contact with natural biodiversity may lead to more public health problems, such as an increase in chronic disease. There is a growing body of research that investigates the impacts of multiple forms of biodiversity on an increasingly diverse set of human health and well-being across scales. With this project, we will systematically map out the existing evidence of biodiversity impacts on human health and well-being. To manage the already huge body of literature, machine learning (both supervised and unsupervised) such as the bespoke classifiers with the large language models, will be applied at the title and abstract screening stage, which will help us filter out the relevant studies and classify them into different biodiversity and health groups.