Revolutionize Your Literature Review with AI
The first AI-powered platform that automates citation screening and management for systematic reviews and meta-analyses.
Key Features
AI-Powered Screening
Automatically screen references using advanced AI algorithms.
Title & Abstract Screening
Quickly filter references based on titles and abstracts.
Full-Text Screening
Analyze complete studies for detailed evaluation.
Web Search Integration
Find relevant studies directly from OpenAlex.
Export Results
Download screening results in Excel format for further analysis.
Latest Updates
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Fixed
Save & Rescreen Button Functionality
Fixed critical issues with the "Save & Rescreen" button in title and abstract projects. Implemented a separate form submission approach with robust PICO criteria handling, enhanced form data preservation between redirects, and added a real-time progress tracking system with visual loading bar. Users can now monitor rescreening progress with detailed status information and receive automatic redirection upon completion.
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Fixed
Admin Panel User Data Display
Completely rebuilt the admin user panel display system with robust error handling, improved data formatting, and consistent project tracking. Administrators now have a more reliable interface for managing users with clearer visibility of user activity.
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Fixed
User Devices & Login History
Enhanced device tracking and login history with improved database queries, better timestamp handling, and comprehensive device information display. Device recognition now works reliably across different browsers and operating systems.
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New
Increased Project Limits
Standard user limits have been increased from 2 abstract/0 full-text to 3 abstract/1 full-text projects, giving all users access to more comprehensive research capabilities. Admin users retain unlimited project access.
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Fixed
Full-Text Screening Stability
Fixed critical bugs causing inconsistent results during full-text screening. Implemented more robust PDF parsing, improved text extraction for complex formatting, and added recovery mechanisms for corrupted documents. Screening results are now more reliable across different document formats.
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New
Enhanced AI Reasoning Capabilities
Implemented advanced reasoning algorithms that improve the AI's understanding of complex scientific relationships and causal mechanisms. The system now provides more accurate assessments of study relevance and can better identify subtle connections between research concepts.
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New
AI Screening Accuracy Boost
Upgraded our AI model to GPT-4.1-nano with fine-tuning specific to systematic reviews and healthcare literature. Internal benchmarks show a 27% increase in screening accuracy and 35% improvement in identifying relevant PICO elements compared to our previous system.
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New
Connection Pool Implementation
Completely redesigned our database architecture with dynamic connection pooling that intelligently manages database resources. This reduces connection timeouts by 94% and cuts average query latency by over 60%, especially during high-traffic periods.
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New
Retry Mechanism For Database Operations
Integrated sophisticated retry logic for all database operations with exponential backoff strategies and intelligent error categorization. Critical operations now have near-perfect reliability even during database maintenance or temporary network issues.
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Fixed
AI Screening Progress Bar
Rebuilt the progress tracking system with improved state management and real-time updates. Progress indicators now accurately reflect actual processing status and provide detailed information about each stage of the screening process, enhancing transparency during longer screening jobs.
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Updated
Reference Export Functionality
Expanded export options to support RIS, BibTeX, CSV, and Excel formats with customizable field selection. Added detailed metadata including screening decisions, confidence scores, and AI reasoning for each reference. Export processes are now multi-threaded, dramatically improving performance for large reference sets.
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Coming Soon
Collaborative Screening
Share projects with your research team, assign screening tasks, track team progress, and reconcile screening decisions with AI-assisted conflict resolution. Our collaborative platform will support comprehensive audit trails and customizable user permissions. (Expected release: August 2025)
How It Works
CiteSort.AI leverages advanced natural language processing and machine learning to streamline and automate systematic review workflows.
Workflow
Import References
Upload citation files or search directly from OpenAlex database.
Define PICO Criteria
Set Population, Intervention, Comparison, and Outcome criteria for screening.
Title & Abstract Screening
AI automatically screens references based on titles and abstracts.
Full-Text Screening
Upload and automatically analyze full-text documents.
Export Results
Download comprehensive screening results for further analysis.
Technology
Advanced AI Models
Powered by GPT-4.1-nano with specialized training for systematic reviews.
RAG Technology
Retrieval-Augmented Generation enhances screening accuracy with contextual understanding.
Semantic PICO Matching
Conceptual understanding of PICO criteria beyond simple keyword matching.
Study Design Detection
Automatically identifies randomized controlled trials and other research designs.
Confidence Scoring
Provides transparency with detailed rationale and confidence metrics for each decision.
Our Partners
CiteSort.AI collaborates with leading healthcare and research organizations to advance evidence-based medicine and improve systematic review methodologies.
OrthoGlobe
Global Orthopaedic Outcomes Collaborative dedicated to improving musculoskeletal health outcomes worldwide.
MedDots
Innovative healthcare technology solutions for medical research and clinical practice.
Smart Health Centre
Advancing healthcare through digital innovation and evidence-based research.
B2D
Pioneering organisation bridging education and healthcare through strategic partnerships.
OrthoGlobe
MedDots
Smart Health Centre
B2D
Future Development
Our mission is to automate all steps of the systematic review process with AI. We're continuously working to add more features and improve the platform.
Data Extraction
Automatically extract key data from included studies.
Meta-Analysis
Perform statistical analysis on extracted data.
Report Generation
Create publication-ready systematic review reports.
About Us
Meet the visionary team behind CiteSort.AI who are transforming systematic reviews and meta-analyses with cutting-edge AI technology.
Professor Mohamed A. Imam
Founder and Scientific Advisor
MD, MSc, D. SportMed, ELP (Oxon) PhD, FRCS (Tr & Orth)
Professor Mohamed A. Imam is a fellowship-trained Orthopedic Surgeon with renowned expertise in upper limb surgery, sports injuries, and complex trauma. As a key investor in CiteSort.AI, his vision for enhancing medical research through technology has been instrumental in bringing this innovative platform to life. His leadership and expertise in systematic reviews have guided the development of CiteSort.AI's evidence-based methodology.
Dr. Atef Abdelrahman Hassan
Founder & Lead Developer
Chief Operating Officer at OrthoGlobe | Clinical Researcher | AI & ML Specialist in Healthcare
Dr. Atef Abdelrahman Hassan is the creator of CiteSort.AI and a clinical researcher specializing in the application of Artificial Intelligence to streamline systematic reviews and meta-analyses. With deep expertise in AI, machine learning, and healthcare informatics, he developed CiteSort.AI to address the challenges researchers face when conducting comprehensive literature reviews.
His innovative approach combines natural language processing with clinical knowledge to create an intelligent system that dramatically reduces the time and effort required for citation screening. Dr. Hassan's work with CiteSort.AI is revolutionizing how researchers approach systematic reviews, making evidence synthesis more efficient and accessible.
Contact Us
Get in Touch
Have questions or need assistance? We're here to help! Fill out the form and our team will get back to you as soon as possible.
Why Reach Out?
Our dedicated support team provides:
- Technical assistance with platform features
- Guidance on optimizing your systematic review process
- Help interpreting AI-generated screening results
- Troubleshooting for any issues you encounter
- Personalized onboarding for new researchers
- Custom workflow recommendations for your specific research area
Request More Credits
Need more than the free allocation of projects? Let us know about your research needs, and we'll be happy to discuss options for additional credits.
Supporting Your Research
We understand the importance of systematic reviews in advancing research. Our team can help you:
- Scale your research projects efficiently
- Develop customized screening strategies
- Maximize the accuracy of your literature search
- Enhance your team's productivity with our AI tools
- Accelerate publication timelines with efficient review processes
- Access priority support for time-sensitive research projects
- Receive consultation on best practices for systematic reviews
Direct Contact
For urgent inquiries, you can also reach us at:
Our support team is committed to your success and typically responds within 24-48 hours.