Join our AI in Evidence Based Healthcare
LinkedIn Group

This group gathers enthusiasts of automation, AI, and machine learning in the context of evidence-based healthcare

ISPOR webinar with Laser AI:
Revolutionizing Systematic Reviews

Learn more about how Artificial Intelligence can help your team complete systematic reviews faster and how AI impacts evidence synthesis.


Publications about the GRADE approach

Introductory series for clinicians published in the BMJ (2008)

Articles with allergy examples published in Allergy (2010)

Grading quality of evidence and strength of recommendations in clinical practice guidelines:

Detailed description of GRADE for authors of guidelines and systematic reviews published in JCE (2011-2015)

Reproducibility of the GRADE approach (2013)

GRADE Handbook

The GRADE handbook describes the process of rating the quality of the best available evidence and developing health care recommendations following the approach proposed by the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) Working Group.
Go to Handbook

GIN-McMaster Guideline Development Checklist

GIN-McMaster Guideline Development Checklist is designed to serve as a publicly available and interactive resource, with links to learning tools and training materials, for those interested in beginning, enhancing or evaluating their guideline development process. Considering items on this checklist is intended to support the development and implementation of trustworthy guidelines.
Go to Checklist

Guidelines developed with GRADEpro GDT

World Health Organization

Allergic Rhinitis and its Impact on Asthma

American Thoracic Society and European Respiratory Society

European Society of Intensive Care Medicine

World Allergy Organization

Osteoporosis Canada

The Surviving Sepsis Campaign Guidelines Committee

The Society of Critical Care Medicine

Ministry of Health of Saudi Arabia (2014/2015)

American College of Rheumatology

American College of Chest Physicians