About the Journal
Applied AI & Data Science for Health, Agriculture & Environment (AIDSAE) is an international peer-reviewed, open access journal that publishes rigorous, applied work at the intersection of artificial intelligence, data science, and real-world problem solving in health, agri-food systems, and environmental sustainability. The journal prioritizes studies that move beyond “toy datasets” to demonstrate measurable value in practice—such as improved decision-making, service delivery, surveillance, diagnostics, early warning systems, precision agriculture, climate and ecosystem monitoring, and risk management—especially in resource-constrained settings.
We welcome original research, implementation reports, methods papers, datasets and benchmarking studies, systematic reviews, and policy/ethics analyses covering (but not limited to) machine learning and deep learning, natural language processing, computer vision, geospatial and remote sensing analytics, time-series forecasting, causal inference, explainable and trustworthy AI, data governance, and responsible AI. Submissions should clearly describe the data source(s), modeling pipeline, validation strategy, reproducibility elements, and practical implications, with attention to fairness, privacy, safety, and ethical use.
AIDSAE is published by EcoScribe Publishers Company Limited and operates continuous publication, providing authors with fast, constructive editorial handling and a focus on transparent reporting standards that support adoption, replication, and policy relevance.
AIDSAE uses double-blind peer review and applies editorial screening to uphold research integrity and reporting quality. All published articles are freely available online. An APC of USD 50 applies only after acceptance (no submission fee).
Ready to submit?
If your work applies AI and data science to solve real problems in health, agriculture, or environmental systems—and is backed by solid validation and transparent reporting—we invite you to submit to AIDSAE.
Submit Manuscript | Checklist for Submission | Contact the Editorial Office
AIDSAE: credible AI and data science—built for real-world impact.
