Farhad Shokraneh
Farhad is an Evidence Synthesis Manager at the University of Oxford, a Post-Doctoral Research Associate at the University of Cambridge, and a Senior Research Associate at Bristol University. In 2016, he founded Systematic Review Consultants LTD.
Having 20 years of experience in evidence synthesis and Evidence-Based Medicine (EBM), Systematic Review Consultants LTD provides consultancy services for a wider range of all review types: Scoping Reviews, Systematic Reviews, Rapid Reviews, Realist Reviews, Umbrella Reviews, Clinical Practice Guidelines, Health Technology Assessment, Clinical Evaluation Report, and Horizon Scanning. The services can be tailored for specific steps: Protocol development, designing & testing search strategy, systematic search & removing duplicates, choosing the right computer program, compatibility check for reporting guidelines such as PRISMA, screening the search results, data extraction, obtaining the full reports, meta-analysis & meta-synthesis, and GRADE.
Responsible Use of AI in Evidence Synthesis: Filling the Gap Between Research and Practice
Responsible Use of AI in Systematic Reviews and Evidence Synthesis
How to Stay Up-To-Date in Your Field
Using AI in Automation of Evidence Synthesis: What Does Research Tell Us?
Episode 3. Kevin and Keith Kallmes - Nested Knowledge
Episode 5. Jos Kleijnen - 40 Years of Systematic Reviews
Episode 4. Carol Lefebvre - The First Librarian & Information Specialist in Cochrane Collaboration
Episode 2. Artur Nowak - Evidence Prime (GRADEpro GDT & Laser AI)
Episode 3. Professor Gordon Guyatt - Story of Evidence-Based Medicine
Episode 2. Jon Brassey - Trip Database
Episode 1. Eitan Agai - PICO Portal
Episode 1. Professor Gene V. Glass - The Story of Meta-Analysis
Utilising AI to Support Systematic Reviews
Using AI and ML in Evidence Synthesis and Systematic Reviews in 2025
Teaching Old Dog New Tricks: Scientometric Mapping for Future Needs of Two Organisations
Using AI in Evidence Synthesis and Systematic Reviews (12 Minutes)
An Introduction to Individual Participant Data (IPD) Meta-Analysis - Professor Richard Riley
Covidence for Screening in Systematic Reviews: 2 Machine Learning (ML) Options & 3 Key Tips Using ML
![Rayyan for Screening for Systematic Reviews - Machine Learning & De-Duplication [RETIRED Version]](https://ricktube.ru/thumbnail/DwnTCS1at8c/mqdefault.jpg)
Rayyan for Screening for Systematic Reviews - Machine Learning & De-Duplication [RETIRED Version]
How to find answers to your clinical questions? Tips for Searching the Literature
Post-Publication Peer-Review (PPPR): 4 Models and The Future of Academic Publishing
How to Avoid Predatory Journals, Publishers & Conferences? How Our Bad Practice Created the Monsters
Should We Say Goodbye to the Academic Journals and Publishers?
GAJET: Good Academic Journal in Ethical Terms
Screening the Search Results for Systematic Reviews: Methods and Semi-Automation Tools
Removing Duplicate Records in EndNote for Systematic Reviews: Semi-Automation of De-Duplication
Computer Programs for Semi-Automation of Evidence Synthesis
Evidence Based Searching and Reporting the Search for Systematic Reviews
Search Strategies for Systematic Reviews: Problems and Solutions
Studification: How to Merge Studies in Review Manager (RevMan) Using Drag and Drop