Call for papers for the Special Issue 2026
Posted on 2025-07-23We would like to inform you that we are accepting submissions for the special issue: Generative AI and Statistical Approaches for Disease Forecasting Across Species.
The submissions will be open from August 1, 2025 to December 30, 2025.
The Special Issue will be publish until June, 2026!!!
The union of generative artificial intelligence (AI) and statistical approaches has brought into being a new wave of exact disease prediction and treatment planning in various biological systems.
When combined with biometrics and statistical inference, these models can produce synthetic data, detect latent risk factors, and model disease trajectories under different settings. This ability is especially important in areas where data unavailability or imbalance is an issue, like diseases of rare occurrence in animals or infections at the initial stages in plants. In plant and animal agriculture and ecological systems, crop or livestock disease outbreaks can cause ruinous effects on economics and the environment. Statistical methods are pivotal in providing fairness, reducing false positives/negatives, and validating predictions across varying populations and species.
Generative AI, augmented with biometric modeling and environmental sensor data, facilitates timely prediction and avoidance of such risks. In veterinary medicine, early forecast of disease aided by generative models assists in the identification of vulnerable animal populations, tracking zoonotic risks and scheduling targeted vaccinations or treatment. It supports the One Health paradigm, which focuses on human, animal and environmental health as interconnected concepts.
Against this background, this research volume seeks to examine the confluence of generative artificial intelligence and statistical methods in pushing disease prediction across species ranging from humans, animals, to plants. The volume seeks to determine the role of applied statistical science, machine learning, and data-driven methods in predictive health in varied biological realms. To these ends, it consolidates a series of empirical and theoretical quantitative and qualitative contributions that leverage methodologies from, among others: biostatistics, computational biology, epidemiology, veterinary and plant sciences, environmental monitoring, biomedical informatics, agricultural data science, and One Health research.
IMPORTANT: Authors must state in the cover letter that this is a submission for the special issue.
Important Dates:
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Initial manuscript submissions: 01.08.2025
Manuscript submissions deadline: 30.12.2025
Revised Papers Due: 31.01.2026
Final notification: 28.02.2026
Special Issue publish until: 30.06.2026
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