SNRI

(ICMIML - 26) | Hybrid Event
18th - 19th October 2026 | Amsterdam, Netherlands

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International Conference on Medical Imaging and Machine Learning
(ICMIML - 26)

18th - 19th October 2026 Amsterdam, Netherlands (Hybrid Event)

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Call for Paper

The ICMIML is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Machine Learning, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Deep learning applications in medical imaging
  • Machine learning algorithms for disease diagnosis
  • Image segmentation techniques in healthcare
  • AI-driven predictive analytics in radiology
  • Ethical considerations in medical AI
  • Integration of imaging modalities with ML
  • Patient data privacy in machine learning
  • Real-time imaging analysis using AI
  • Novel feature extraction methods for imaging
  • Transfer learning in medical image classification
  • Automated detection of tumors using ML
  • Challenges in medical data annotation
  • Interpretable machine learning in healthcare
  • Comparative studies of imaging techniques
  • Impact of AI on radiologist workflows
  • Machine learning for personalized medicine
  • Data augmentation strategies for medical images
  • Clinical validation of machine learning models
  • Use of GANs in medical imaging
  • Future trends in medical imaging technology
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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