integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modelling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields.
Methods: In this review we collect and explain over one hundred terms related to Systems Medicine. These include both modelling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references.
Results: This glossary aims at being a first aid kit for the Systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for keep digging into the topic.
|Journal||Network and Systems Medicine|
|Publication status||Accepted/In press - 27 Oct 2020|
- Graphs and Networks
- machine learning
- Systems medicine
- multi-scale modelling
- multi-scale data science