(ICDAPMT - 26) | Hybrid Event
15th - 16th May 2026 | Singapore, Singapore

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International Conference on Data Analytics and Predictive Modeling Techniques
(ICDAPMT - 26)

15th - 16th May 2026 Singapore, Singapore (Hybrid Event)

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Call for Paper

The ICDAPMT 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 Statistics,Data Science, 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:

  • Predictive modeling techniques in analytics
  • Data analytics for business intelligence
  • Statistical methods for predictive analytics
  • Machine learning in predictive modeling
  • Big data analytics for decision making
  • Predictive analytics in healthcare
  • Data visualization for predictive insights
  • Statistical modeling for customer behavior
  • Predictive analytics in marketing strategies
  • Data-driven approaches to risk management
  • Predictive modeling for financial forecasting
  • Real-time predictive analytics applications
  • Ethics in predictive modeling practices
  • Statistical techniques for anomaly detection
  • Data analytics for operational efficiency
  • Predictive analytics in social sciences
  • Integrating predictive modeling with AI
  • Future trends in predictive analytics
  • Statistical learning for predictive insights
  • Applications of predictive modeling in industry
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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