Fwd: MICCAI meets Africa Workshop 2024 Call for papers
Abraham Owodunni
From: Celia Cintas <Unknown>
Date: Monday, April 8, 2024 at 3:03:59 PM UTC+1
Subject: MICCAI meets Africa Workshop 2024 Call for papers
To: Machine Learning and Data Science Africa Network <Unknown>
MICCAI meets Africa Workshop 2024
Call for papers
Over recent years, there has been considerable excitement about the extraordinary opportunities that machine learning (ML) may offer in the healthcare of tomorrow. Given the potential of ML technology in facilitating the quantification of large and complex datasets, medical imaging has witnessed rapid and revolutionary developments. However, a limitation of current ML developments for medical imaging is that they have overwhelmingly and almost entirely targeted imaging applications in high-income settings. Hence, it is important to promote and accelerate the development of trustworthy and accessible ML solutions for medical imaging in low-to-middle-income (LMIC) countries to advance global healthcare.
This workshop aims to connect researchers, medical experts, policymakers, and regulators from Africa and beyond to share experiences and initiatives in promoting ML for medical imaging on the African continent, by Africans for Africans. With this workshop, we hope to showcase exceptional research done on the continent, raise awareness about initiatives, attract collaborators, promote new research and innovation in the field to address Africa-specific healthcare challenges and encourage similar initiatives for promoting practical ML solutions for resource-limited settings around the world.
Core Focus Areas
Overcoming Healthcare Barriers in LMICs:
Address poor imaging quality, scan completeness, and data sharing challenges.
Utilise affordable X-rays, ultrasound, and smartphone diagnostics.
Deploy biosignals like EEG and ECG for cost-effective diagnoses.
Propose low-cost image-guided therapies and computer-integrated interventions
Methodological Advances in ML:
Enhance image quality with innovative techniques for low-cost devices.
Develop data-efficient ML models suited for LMICs' sparse data environments.
Implement robust strategies for handling missing and noisy data.
Apply cost-effective transfer learning and domain adaptation.
Focus on AI model bias mitigation and model compression for equity and resource efficiency.
Driving ML Innovations for Improved Care:
Tailor ML algorithms to meet specific medical imaging challenges in LMICs.
Advance early disease detection and monitoring with minimal resources.
Leverage multimodal data for predictive analytics in patient management.
Evaluate ML's impact on healthcare access and policies in LMICs.
Accelerate the adoption of ML innovations for sustainable healthcare improvements.
Develop solutions to manage data scarcity and optimise computational resources.
Submission Guidelines
Submissions are invited in two formats: short papers (4 pages, including references) or long papers (8 pages of content plus 2 pages for references). Accepted long papers will be included in the workshop proceedings, which will be published under the LNCS Springer series. Consequently, submissions for long papers must adhere strictly to the Springer LNCS format to ensure consistency across the proceedings. The MICCAI meets Africa Workshop review process will be double-blind; authors are therefore required to anonymize their submissions to prevent identification. Each submission will be rigorously reviewed by at least three external reviewers to assess its suitability for the workshop program. Accepted short and long papers can be submitted to preprint repositories such as arxiv. Authors can post the submitted version to arxiv, but cannot post the camera-ready version published under Springer LNCS to arxiv during the publication embargo period, according to Springer’s License to Publish. Authors can include a link to the LNCS version on arxiv when the SpringerLink becomes available.
Submission Instructions:
Authors are required to submit their papers electronically, adhering strictly to the Springer LNCS style guidelines. Templates for LaTeX and MS Word are available on the Lecture Notes in Computer Science website. Modifications to the template are not allowed, and failure to comply with these formatting guidelines will result in the paper's rejection.
Please submit your papers through the Submission Portal:
https://cmt3.research.microsoft.com/MICCAImeetsAFRICA2024/
Important Dates:
Full Paper Submission Deadline: 24 June 2024, 11:59 PM EST
Notification of Acceptance: 15 July 2024
Camera-ready Submission: TBA
Workshop Date: 6 October 2024