CiteSort.AI was born from a simple idea: researchers shouldn't spend weeks doing what AI can accomplish in minutes.
To democratize systematic reviews by making AI-powered screening accessible to every researcher, regardless of budget or technical expertise. We believe high-quality evidence synthesis should be efficient, accurate, and available to all.
A world where systematic reviews are completed in days instead of months, where AI augments human expertise to produce more comprehensive and accurate evidence syntheses, advancing medicine and science faster than ever before.
Pioneering the future of evidence-based medicine through innovation and expertise

Main Founder & Lead Developer
Dr. Atef Abdelrahman Hassan is the main founder, visionary creator and architect behind CiteSort.AI, bringing together his unique blend of clinical research expertise and advanced artificial intelligence specialization. With deep expertise in AI, machine learning, and healthcare informatics, he developed CiteSort.AI to revolutionize systematic literature reviews.

Main Founder & Scientific Advisor
Professor Mohamed A. Imam is a fellowship-trained Orthopaedic Surgeon and Professor of Digital Health with internationally recognized expertise in upper limb surgery, sports injuries, and complex trauma management. As Executive Medical Director at Smart Health Centre and a key visionary behind CiteSort.AI, he recognized the critical need to streamline the systematic review process.
The principles that guide everything we do at CiteSort.AI
Pushing boundaries with cutting-edge AI technology
Dedicated to advancing medical research globally
Working together with researchers worldwide
Committed to the highest quality standards
Collaborating with leading organizations to advance research

Global Orthopaedic Outcomes Collaborative

Healthcare Technology Solutions

Digital Health Innovation

Education & Healthcare Partnership
Our roadmap to fully automate the systematic review process
AI-powered automatic extraction of key data from included studies
Statistical analysis with forest plots and publication bias detection
PRISMA-compliant systematic review reports generated automatically