Where rigorous research meets
public health practice.

Frontiers in Emerging Artificial Intelligence and Machine Learning is an international, open-access, peer-reviewed journal dedicated to publishing high-quality research, innovative methodologies, emerging technologies, and significant developments in the rapidly evolving fields of artificial intelligence (AI) and machine learning (ML). The journal provides a global scholarly platform for researchers, academics, industry experts, technology professionals, and practitioners to present original research, exchange innovative ideas, and contribute to the advancement of intelligent technologies and data-driven systems. It welcomes research that explores theoretical foundations, computational methods, practical applications, and emerging challenges associated with modern artificial intelligence and machine learning.

The journal encourages contributions covering a broad range of topics, including machine learning, deep learning, natural language processing, computer vision, reinforcement learning, generative artificial intelligence, intelligent automation, explainable AI, data-driven decision-making, neural networks, predictive analytics, robotics, and AI-enabled applications. By bringing together interdisciplinary perspectives from computer science, engineering, mathematics, data science, and related fields, the journal aims to promote meaningful collaboration and support the development of innovative and responsible intelligent systems.

We follow a rigorous double-blind peer-review process, ensuring that all submitted manuscripts are evaluated fairly, objectively, and confidentially by at least two independent reviewers with relevant expertise. The review process is designed to maintain high standards of academic integrity, originality, scientific quality, methodological soundness, and relevance. Reviewers provide constructive academic feedback to help authors strengthen their manuscripts while ensuring that published research meets appropriate scholarly and ethical standards.