====== Evidencio ======
At Evidencio, we strongly believe that prediction models can complement human clinical decision-making and assist healthcare professionals in making patient-tailored evidence-based decisions. It is our mission to support the transition of these clinical prediction models from research into everyday medical practice.

To reach our goal, we are building a platform and research community which together provide a dynamic, high-quality, and transparent library filled with clinically relevant prediction models.

**Background**\\
In the last few decades, the volume of scientific papers has increased exponentially. The resulting 'big data' pool houses an enormous potential, but is still only marginally used in medical practice. The World Health Organization (WHO) has acknowledged this disconnect between science and medical practice as the "know-do gap". Improvement of knowledge extraction, validation, and transferral is essential in order to utilize the untapped potential of medical databases such as PubMed and EMBASE. It was this insight that moved the developers of Evidencio to found the online research community Evidencio in 2015.

In addition to scientific papers, the number of published medical prediction models also steeply increased over the years. Prediction models are research-based tools that assist healthcare professionals in making evidence-based medical decisions and are a powerful way to translate scientific literature into medical practice. When appropriately developed and validated, prediction models have inherent advantages over human clinical decision making. Firstly, the statistical models can accommodate many more factors than the human brain is capable of taking into consideration. Secondly, if given identical data, a statistical model will always give the same result whereas human clinical judgment has been shown to result in both inconsistency and disparity, especially with less experienced clinicians. Thirdly, and perhaps most importantly, several prediction models have been shown to be more accurate than clinical judgment alone.

Prediction models can be applied in various settings, for example to describe the likelihood of the presence or absence of a certain condition, assist in determining patient prognosis, and help classify patients for treatment. The use of prediction models not only eliminates the distorting effect of subjectivity, but also sets the stage for true informed consent and shared decision-making. In addition, several clinical studies have shown that the use of prediction models leads to shorter hospital stays, fewer complications, cost savings, and a better allocation of scarce resources.

Please note: Although the added value of medical prediction models is obvious, these models are not a replacement for clinical judgment and should complement rather than supplant clinical opinion and intuition.
This page contains the user manual of Evidencio tools and shows you exactly how to use all the tools provided by Evidencio. 

**//Click on one of the topics below to find out more about Evidencio//**

===== Join the Evidencio community =====
[[signing_up|Join the Evidencio community]]: A personal Evidencio account is free, with no strings attached! Join us and help create clarity, transparency, and efficiency in the creation, validation, and use of medical prediction models.

===== Find and use a model online =====
[[Find/use model|Find and use a model online]]: Evidencio hosts over 600 medical prediction models. More than 250 of these models are available as public models. 

**Tip**: You can navigate to the Evidencio home page from anywhere on the platform by clicking on the 'Evidencio logo' or the 'Evidencio heart' in the top menu bar.

===== Add a model =====
[[Creating a model|Create]] and publish your own prediction models. Find out more about specific model types: 
  * [[linear_model|Linear model]]
  * [[logistic_regression|Logistic regression model]]
  * [[survival_regression|Survival regression model]]
  * [[cox_regression|Cox proportional hazard regression model]]
  * [[Custom model|Custom model]]
  * [[R script based model|R script based model]]

===== Create a composite model =====
With [[creating_a_composite_model|composite models]] it is possible to combine multiple models and calculate multiple predictions based on a single set of input parameters in one go. 

===== Validate a model =====
With the [[validating_a_model|validation tool]] it is easy to copy and paste cohort data from excel or comparable spreadsheet software to quickly validate online models with your own data.