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International Conference on AI and Big Data in Biomedical Engineering - (ICABDBE-26)

26th - 27th December 2026 , Chicago - USA

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Call For Papers

The (ICABDBE-26) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Artificial Intelligence,Data Science,Bioinformatics are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • AI applications in biomedical engineering
  • Machine learning for medical device innovation
  • Predictive modeling in biomedical engineering
  • Integration of AI in healthcare technologies
  • AI for personalized biomedical solutions
  • Ethical considerations in biomedical engineering
  • Case studies of AI in biomedical devices
  • AI for improving patient outcomes in engineering
  • Challenges in AI for biomedical applications
  • AI in telehealth and remote monitoring
  • Collaborative projects in biomedical engineering
  • AI for optimizing medical imaging techniques
  • Future directions in biomedical engineering
  • AI-enhanced biomedical data analysis
  • Machine learning for wearable health technologies
  • AI in rehabilitation engineering applications
  • AI for improving surgical outcomes
  • Integration of robotics in biomedical engineering
  • AI in prosthetics and assistive devices
  • AI for enhancing biomedical research methodologies

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.