Hybrid Conference (In Person / Virtual)

International Conference on Predictive Analytics and Decision Support Systems (ICPADSS - 27)
23rd - 24th March 2027 , Matola, Mozambique
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Call For Papers

The ICPADSS provides a supportive platform for both experienced researchers and early-career academicians to present their work and gain recognition.

The conference covers diverse topics such as Computational Science, Data Science, encouraging participation from emerging researchers and fostering academic growth.

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

01
Predictive analytics in healthcare applications
02
Decision support systems for smart cities
03
Machine learning techniques for decision making
04
Data-driven approaches for predictive modeling
05
Real-time analytics for business intelligence
06
Risk assessment using predictive analytics
07
User-centered design in decision support systems
08
Ethical implications of predictive analytics
09
Big data challenges in decision support
10
Integrating AI into decision-making frameworks
11
Case studies in predictive analytics success
12
Visualization techniques for predictive insights
13
Impact of data quality on predictions
14
Collaborative decision-making systems
15
Predictive analytics in supply chain management
16
Machine learning for risk mitigation strategies
17
Evaluating the effectiveness of decision support
18
Trends in predictive analytics research
19
Future directions in decision support systems
20
Interdisciplinary approaches to predictive analytics

Assessment

Submissions will be reviewed to ensure quality and relevance, with a focus on encouraging emerging research contributions. Accepted papers will be presented and considered for publication opportunities.

Registration

Early-career researchers are encouraged to register and present their work, gaining valuable feedback and academic exposure.

Publication

The conference provides opportunities for emerging researchers to publish their work in recognized platforms.