WeChat Mini Program
Old Version Features

[Exploration of the Classification of Public Health Intervention and Its Implication for China].

Z,Y H Zhao, Z Y Zhang,E Y Gong,R T Shao

Zhonghua yu fang yi xue za zhi Chinese journal of preventive medicine(2023)

School of Population Medicine and Public Health

Cited 0|Views11
Abstract
Public health interventions refer to a series of organized and specific measures implemented in specific situations to achieve goals related to improving health, preventing and controlling diseases, and more. As research on intervention measures has deepened, the classification of public health interventions has gradually developed, clarifying the nature, categories and intervention targets of these measures. This typological study can help standardize the concepts of public health interventions, develop, select, and evaluate the effectiveness of intervention measures, and improve the effectiveness of public health actions. This paper reviews the main international classification models of intervention measures, analyzes and summarizes five classification methods of public health interventions, namely, based on goals, nature, objects, hierarchies, and modes of action, and introduces relevant cases. The paper proposes that China should conduct further in-depth and systematic research on public health interventions, develop evidence-based intervention measures and practices, promote the effective transformation of intervention measures and results, and facilitate the development of public health.
More
Translated text
Key words
Public health,Intervention,Classification
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined