1st MICCAI Workshop  ·  MICCAI 2026

Advancing African Medical AI
through Global Integration

Advancing African Medical AI through Global Integration

The AFRICAI 2026 workshop is the annual meeting of MICCAI’s Special Interest Group on African Medical Imaging AI (SIG AFRICAI). It brings together researchers, clinicians, and practitioners working on medical imaging AI in African health systems. Rather than treating Africa as a low-resource setting in isolation, AFRICAI focuses on scientific collaboration, clinical relevance, and African-led research as key building blocks for globally robust and trustworthy medical AI.

AFRICAI fills an important gap within MICCAI: the lack of structured, multi-site validation and deployment discussions focused on African health systems. By putting clinical integration and real-world performance at the centre, the workshop aims to set standards for evaluating imaging AI in underrepresented populations — a challenge that is increasingly relevant to global regulatory and translational efforts.

The workshop will spotlight high-burden and underrepresented conditions, including tuberculosis, paediatric pneumonia, obstetric imaging, and point-of-care technologies. We welcome contributions on clinical validation, prospective evaluation, deployment studies, and research infrastructure. Beyond a scientific forum, AFRICAI serves as a lasting platform to embed African clinical expertise, technical innovation, and cultural diversity into the core of trustworthy medical AI — positioning African-led research as a foundational contributor to globally equitable healthcare.

Call for Papers

The AFRICAI 2026 workshop invites submissions describing original methodological contributions, system architectures, and rigorous validation studies. We specifically encourage work that addresses the unique challenges of Global Integration through the following tracks. Methods such as federated learning, edge AI, and domain generalization are welcome when embedded within these clinical and deployment-driven themes. Submissions will be through OpenReview and all entries will go through a double-blind peer-review process. Topics include but are not limited to:

• Clinical Robustness & Human-Centric Evaluation: Benchmarking model generalizability across diverse African clinical centers to mitigate domain shift, coupled with rigorous analysis of Human-AI interaction, decision support efficacy, and workflow integration in real-world settings.
• Trustworthy & Explainable AI (XAI): Interpretability methods designed to align with local clinical heuristics, aiming to bridge the gap between “black box” model outputs and clinical trust in diverse healthcare systems.
• Africa-Specific Clinical Applications: TB/HIV imaging, Maternal & neonatal imaging, Pediatric infectious disease, Sickle cell, endemic conditions.
• Cross-Site Validation & Benchmarking in African Health Systems: Multi-country evaluation, domain shift within Africa, and prospective trials.
• Deployment Science & Health-System Integration: Workflow integration, decision-support impact, real-world failure analysis.
• Ethical Data Stewardship & Governance in African Contexts: Consent models, cross-border governance, regulatory harmonization.

If you have any questions about the AFRICAI workshop or the submission process, please reach out to Marawan Elbatel and Cecilia Kessler.

Organising Committee

Karim Lekadir

Universitat de Barcelona, Spain

Cecilia Kessler

Universitat de Barcelona, Spain

Marawan Elbatel

The Hong Kong University of Science and Technology, Hong Kong

Farah Shamout

NYU Abu Dhabi, UAE

Aya Yassin

Ain Shams University, Egypt

Sahar Selim

Nile University, Egypt

Tanya Akumu

Universitat de Barcelona, Spain

Yunusa Muhammed

Gombe State University, Nigeria

Hussein Twabi

Kamuzu University of Health Sciences, Malawi

Mamadou Bousso

Université de Thiès, Senegal

Geoff Lavoy

Infectious Diseases Research Collaboration, Uganda

Xiaomeng Li

The Hong Kong University of Science and Technology, Hong Kong

Concetto Spampinato

University of Catania, Italy

Federica Proietto Salanitri

University of Catania, Italy

Submission Guidelines

Format: Papers will be submitted electronically following Lecture Notes in Computer Science (LNCS) style of up to 8 + 2 pages (same as MICCAI 2026 format). Submissions exceeding the page limit will be rejected without review. LaTeX style files can be found from Springer. The file format for submissions is Adobe Portable Document Format (PDF). Other formats will not be accepted. Please refer to the MICCAI 2026 Paper Submission Guidelines for full details.

Double Blind Review: AFRICAI reviewing is double blind. Please review the anonymity guidelines of MICCAI and confirm that the author fields do not break anonymity.

Paper Submission: AFRICAI uses OpenReview for online submission.

Supplemental Material: Supplemental material submission is optional, following the same deadline as the main paper. Contents of the supplemental material should be referred to appropriately in the paper; reviewers are not obliged to read them.

Submission Originality: Submissions should be original. No paper of substantially similar content should be under peer review or accepted for publication elsewhere (conference/journal, not including archived work).

Proceedings: The proceedings of AFRICAI 2026 will be published as part of the joint MICCAI Satellite Events proceedings with Springer (LNCS), open access through the MICCAI Society pages.

Review Process

• All papers will be reviewed following a rigorous double-blind review process with at least 3 independent reviewers per submission with relevant domain expertise.
• OpenReview’s automated conflict-of-interest (COI) detection system will be used, supplemented by manual verification by the Organizing Committee. Reviewers will be barred from reviewing papers from recent collaborators, current/former institutions, or co-authors.
• Any submission from an Organizing Committee member will be managed by an independent Area Chair to ensure an unbiased decision.
• Final selections will be based on technical merit, clinical relevance, and adherence to the workshop’s scope. Outstanding papers will be selected for oral presentation.
• We will select reviewers from a pool of reputable researchers spanning medical imaging, clinical AI, deployment science, and global health, with particular attention to geographic and career-stage diversity.