AIDA
AI-assisted Diagnostics and Analytics
Pioneering the future of healthcare through advanced artificial intelligence and machine learning. Our interdisciplinary collaboration between Computer Science and Medical School is revolutionizing diagnostic accuracy and patient care outcomes.
About AIDA
Our Mission
AIDA represents a groundbreaking initiative that bridges cutting-edge computer science research with clinical medical expertise. We are developing next-generation AI-powered diagnostic tools that enhance healthcare delivery and improve patient outcomes worldwide. A key area of focus is histopathological diagnostics, where we are creating advanced AI applications for screening and supporting pathology reporting.
Do you want to access the platform?
The platform will be made accessible in Summer 2026, but in the meanwhile you can take a look to partial code and publications here.
Platform Vision
AIDA will be two things: 1) a collaborative platform, where complex cases can be accessed and annotated by experts worldwide, supporting the pursuit of true ground truth, and 2) an AI-assisted platform, where annotated data are used to train AI systems that support human decision-making.
AIDA will provide reporting solutions that integrate human expertise with AI reasoning, driving research in digital pathology and providing an outstanding training resource for pathology education.
The AIDA system will empower pathologists by analyzing complex morphological patterns, uncovering subtle diagnostic features, and significantly streamlining the workflow. Grounded in rigorous research and clinical validation, our team is building intelligent systems that transform complex medical data into meaningful insights.
Platform Architecture
The Platform
A web-based collaborative platform, accessible by certified medical practitioners, moderated by both systemic agents and human moderators, guaranteeing complete security on anonymized data, for a privacy-by-design system.
The AI Engine
Recent advances in multimodal learning, published in top-tier venues such as ICCV, CVPR, and SIGGRAPH, are leveraged to make the annotation process more engaging, faster, and richer. Cutting edge solutions in Natural Language Modeling, incremental few shot learning, structured learning will be the main keywords characterizing our engine.
The Data
AIDA will consider both public datasets, in order to enrich them at an unprecedented level of details, plus very rare diseases are shared to promote collaborative reasoning on unresolved cases.
Research Areas
Medical Image Analysis
Advanced deep learning algorithms for automated analysis of histopathological images with superhuman accuracy in detecting anomalies and diseases. Our systems are designed to extract meaningful information from complex morphological patterns and to uncover diagnostic, prognostic, and predictive factors through different levels of supervision.
Forensic Applications
Transforming forensic histopathology with AI and digital pathology, combining precision and standardization to enhance the reliability of medico-legal practice. We aim to establish reproducible protocols and foster international best practices.
Collaborative Digital Pathology
A global collaborative platform where medical images, annotations, and expertise can be shared with AI-powered tools for histopathological screening, annotation, and reporting support. Social choice theory for bringing multiple opinions to a single report.
Privacy-by-Design
Privacy-preserving machine learning techniques that enable collaborative model training across multiple healthcare institutions without sharing sensitive patient data. Implementing federated learning approaches and advanced encryption methods to ensure data security while advancing medical AI research.
Leadership Team
Research Team
Faculty Members
PhD Students
Collaborative Excellence
Our interdisciplinary team includes PhD students, postdoctoral researchers, and clinical fellows from both Computer Science and Medical departments. Through weekly joint meetings, shared laboratory spaces, and co-mentorship programs, we ensure seamless integration of technological innovation with clinical expertise.
Contact Us
Get in Touch
marco.cristani@univr.it
Location
stefano.tinazzimartinigobbo@univr.it
Location
University of Verona
location
Publications
Our Research Contributions and Impact
Project Timeline
AIDA's Journey from Concept to Implementation
AIDA Project Launch
Established interdisciplinary collaboration between Computer Science and Medical School departments. Secured initial $2.5M funding from NSF and NIH. Set up shared research infrastructure and recruited core team members.
Data Partnership Agreements
Signed data sharing agreements with 8 major healthcare institutions. Established comprehensive privacy protocols and IRB approvals. Began collection of diverse medical datasets totaling over 500,000 patient records.
Core Algorithm Development
Developed foundational deep learning architectures for medical image analysis. Created novel federated learning protocols for healthcare applications. Published first proof-of-concept results showing 92% diagnostic accuracy.
First Clinical Validation
Completed initial clinical trials at partner hospitals. Validated AI models on real patient data with clinical oversight. Achieved breakthrough 95% accuracy in diagnostic imaging tasks, surpassing human specialist performance.
Multi-Modal Integration
Successfully integrated multiple data types including imaging, lab results, and clinical notes. Developed comprehensive NLP pipeline for processing unstructured medical text. Expanded diagnostic capabilities to 15+ medical conditions.
Explainable AI Framework
Launched interpretable AI component providing transparent diagnostic reasoning. Implemented clinical decision support interface trusted by healthcare professionals. Received FDA breakthrough device designation for key diagnostic modules.
Large-Scale Deployment
Deployed AIDA systems in 5 major medical centers serving over 100,000 patients. Integrated seamlessly with existing electronic health record systems. Demonstrated significant improvements in diagnostic speed and accuracy.
International Expansion
Extended AIDA deployment to international partner institutions in Europe and Asia. Adapted models for diverse populations and healthcare systems. Established global research consortium with 25+ institutions worldwide.
Next Generation Platform
Currently developing AIDA 2.0 with advanced multimodal AI capabilities. Implementing real-time patient monitoring and predictive analytics. Planning expansion to 50+ healthcare institutions and targeting 1M+ patient impact by end of 2025.