Hybrid Conferencee

International Conference on Data Science in Biomedical Engineering (ICDSBME - 26)

22nd - 23rd September 2026 | Shanghai, China

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Conference Notifications:

"Be sure to check this section regularly for all Research Plus International Conference updates. We’ll keep you informed about deadlines, event details, and more important notifications."

Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Shanghai. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Shanghai event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Shanghai conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Shanghai, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Shanghai."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICDSBME aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Data Science, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

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

01
Data science applications in healthcare
02
Machine learning for biomedical data analysis
03
Predictive modeling in biomedical engineering
04
Data-driven decision making in healthcare
05
Case studies in biomedical data science
06
Challenges in healthcare data management
07
Real-time data processing in healthcare
08
Data visualization techniques for biomedical data
09
Ethical considerations in biomedical data usage
10
Collaborative tools for healthcare data analysis
11
Future trends in biomedical data science
12
Data integration in healthcare systems
13
User experiences with healthcare data tools
14
Data mining techniques in biomedical research
15
Impact of AI on biomedical engineering
16
Data quality assessment in healthcare data
17
Telemedicine and data science applications
18
Data-driven innovations in medical devices
19
Patient-centered data science approaches
20
Benchmarking biomedical data methodologies