Abstract

Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling 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 more than100 terms related to Systems Medicine. These include both modeling 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 digging into the topic.

Highlights

  • Death has always been the end of every human’s life, mankind has been trying to delay that as much as possible

  • Background: Systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment

  • Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields

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Summary

Medicine Terminology

Massimiliano Zanin,1,* Nadim A.A. Aitya,[2] Jose Basilio,[3] Jan Baumbach,[4] Arriel Benis,[5] Chandan K. Behera,[2] Magda Bucholc,[2] Filippo Castiglione,[6] Ioanna Chouvarda,[7] Blandine Comte,[8] Tien-Tuan Dao,[9,10] Xuemei Ding,[2] Estelle Pujos-Guillot,[8] Nenad Filipovic,[11,12,13] David P. McClean,[20] Niamh McCombe,[2] Joao Luıs de Miranda,[21,22] Mihnea Alexandru Moisescu,[23] Francesco Pappalardo,[24] Annikka Polster,[25] Girijesh Prasad,[2] Damjana Rozman,[26] Ioan Sacala,[23] Jose M.

Introduction
Complex networks
Decision support systems
Deep learning
Digital Health
If p
Graph embedding
Network Analysis Software
Full Text
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