Aims and Scope
African Multidisciplinary Journal of Sciences and Artificial Intelligence publishes peer-reviewed research that integrates scientific inquiry and artificial intelligence to address complex contemporary challenges. The journal welcomes multidisciplinary studies that combine domain knowledge, computational intelligence, data-driven methods, and applied scientific research to produce theoretically meaningful, methodologically rigorous, and socially relevant contributions across diverse sectors and contexts, including African and global settings.
Multidisciplinary Science Artificial Intelligence Data-Driven Research Innovation & Impact Ethics & Governance
Aims
Bridge Science and Artificial Intelligence
Publish research that meaningfully connects scientific domains with AI, machine learning, and computational methods.
Address Real-World Problems Through Multidisciplinary Integration
Support studies that respond to societal, environmental, educational, health, industrial, and developmental challenges using rigorous cross-disciplinary approaches.
Promote Responsible and Explainable Innovation
Encourage transparent, ethical, and context-sensitive AI applications with clear validation, limitations, and governance considerations.
Advance Capacity for Evidence-Informed Decision-Making
Disseminate research that improves prediction, modeling, monitoring, and intelligent support systems for practice and policy.
Authors are encouraged to specify the disciplinary domains involved, the role of AI or computational intelligence, the dataset and validation approach, ethical safeguards, and the practical significance of the findings.
Scope
The journal considers original research, applied AI studies, scientific and computational modeling papers, intelligent system development, methodological contributions, data papers, technical notes, conceptual analyses, and systematic or scoping reviews at the intersection of sciences and artificial intelligence. Submissions should demonstrate multidisciplinary relevance, transparent methods, strong validation, and appropriate ethical and governance considerations.
1) AI for Natural, Physical, and Life Sciences
Artificial intelligence and data-centric methods applied to biology, chemistry, physics, environmental science, agriculture, and related scientific fields.
2) Machine Learning, Deep Learning, and Intelligent Algorithms
Algorithm development, predictive modeling, pattern recognition, optimization, computer vision, natural language processing, and hybrid intelligent systems.
3) Health, Biomedical, and Public Health Intelligence
Clinical decision support, biomedical analytics, digital health, epidemiological modeling, diagnostics, and health systems intelligence with ethical safeguards.
4) Engineering, Robotics, and Smart Systems
Automation, robotics, smart devices, cyber-physical systems, industrial AI, control systems, and engineering applications of intelligent computation.
5) Education, Social, and Behavioral Analytics
Learning analytics, educational AI, computational social science, behavioral modeling, digital society studies, and public-sector intelligence applications.
6) Agriculture, Environment, and Sustainability Informatics
Precision agriculture, climate analytics, biodiversity monitoring, disaster prediction, sustainability modeling, and environmental decision support.
7) Data Governance, Explainability, and AI Ethics
Bias, fairness, transparency, accountability, human-centered AI, governance frameworks, and responsible deployment in diverse contexts.
8) Multidisciplinary Reviews and Methods
Benchmark datasets, reproducible pipelines, integrative methods, and evidence syntheses bridging scientific disciplines and AI.
Types of Manuscripts Considered
The journal considers, among others: original research articles, multidisciplinary empirical studies, AI model development papers, intelligent system design studies, data and benchmark papers, computational and simulation studies, technical and methodological notes, conceptual and policy analyses, and systematic or scoping reviews with transparent procedures. Submissions must articulate the scientific and AI contribution clearly, report methods transparently, and discuss ethical and practical implications responsibly.
African Multidisciplinary Journal of Sciences and Artificial Intelligence fosters internationally relevant and ethically grounded scholarship that integrates science and artificial intelligence to generate robust knowledge, practical innovation, and meaningful societal benefit.