… veil of unknown causes diseases; the single cause biological specific causation theory and
Koch's law came out, which opened the "golden era" of epidemiological causal inference. …

… causal inference and its three analytical frameworks, namely, counterfactual framework (CF),
potential outcome framework (POF), and structural causal … scenarios of causal inference in …

… variants to develop causal inferences from … ) to infer the causal relation between the phenotype
and the risk of diseases. In recent years, MR approach is widely used in causal inference …

… of confounding and reserve causation regarding Mendelian … Mendelian randomization
studies in causal inference is also subject … , and interpretation on causal inference that related to …

… In this paper, under both causal thinking and diagram, the real and measured cross-… One
of the common preconditions for causal inference in such studies is that:there must be a causal …

… Starting from causal thinking, this paper divides the time axis in nature into three time … of
both a real cause and a real effect. This has anchored that causal inference can only be realized …

… Application of directed acyclic graphs in identification and control of selection bias in causal
inference[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2019, 23(3): …

: 当今互联网, 云计算和物联网技术的成熟和发展, 医疗/卫生信息化的广泛普及, 使得医疗/卫生
相关数据正在以惊人的速度增长; 同时, 组学技术(基因组, 影像组等) 的推广应用, 以及可穿戴移动…

… number of people to make causal inferences. The formation of the … causal inference research
should be unified based on the time of the occurrence or beginning of a postulated cause…

… Challenges and factors that influencing causal inference and interpretation, based on
Mendelian randomization studies [J]. Chinese Journal of Epidemiology, 2020, 41(8): 1231-1236. …