Abstract
Artificial intelligence (AI) is rapidly reshaping nearly every domain of medicine, from diagnostics and clinical decision support to operational workflows and biomedical discovery. Despite this rapid expansion, the translation of AI methods into clinically meaningful, ethical, and reproducible medical practice remains uneven. The Journal for Artificial Intelligence in Medicine (JAIM) is launched to serve as a dedicated, interdisciplinary forum focused on the rigorous development, evaluation, and implementation of AI technologies in healthcare. This inaugural editorial outlines the motivation, scope, and vision for JAIM as a platform that bridges engineering innovation with clinical reality.
Introduction
Artificial intelligence has transitioned from a theoretical tool to a practical force in modern medicine. Machine learning models now assist with image interpretation, risk stratification, natural language processing of clinical notes, and operational optimization across healthcare systems. Yet, enthusiasm for AI frequently outpaces clinical validation, regulatory readiness, and real-world integration.
The gap between algorithmic performance and patient-centered impact remains a defining challenge. Many promising AI tools fail to generalize, lack transparency, or are insufficiently aligned with clinical workflows. These challenges underscore the need for a scholarly venue that prioritizes translational rigor, interdisciplinary collaboration, and responsible deployment.
The Journal for Artificial Intelligence in Medicine is founded to address this need.
Scope and Mission
JAIM aims to publish work at the intersection of medicine, engineering, and data science with a clear emphasis on clinical relevance. The journal welcomes contributions spanning, but not limited to:
- Clinical applications of AI and machine learning
- Validation and generalizability of medical AI systems
- Human–AI interaction in clinical environments
- Ethical, legal, and regulatory considerations
- AI-enabled medical devices and digital therapeutics
- Health system integration and implementation science
By fostering dialogue between clinicians, engineers, researchers, and policymakers, JAIM seeks to accelerate the responsible translation of AI innovations from concept to bedside.
Commitment to Rigor and Transparency
JAIM is committed to methodological rigor, transparency, and ethical clarity. Submissions will be evaluated with attention to reproducibility, data provenance, clinical validity, and alignment with patient safety principles. While the journal embraces innovation, it equally values negative results, real-world deployment studies, and lessons learned from failed implementations.
Foundational editorials and perspectives may be authored by members of the editorial leadership, with full disclosure. Peer-reviewed research submissions will be handled under blinded editorial processes to ensure fairness and integrity.
Looking Ahead
The launch of JAIM represents an invitation to the broader medical and engineering communities to shape the future of AI in healthcare collaboratively. As the field evolves, the journal will adapt to emerging challenges and opportunities, serving as both a scholarly record and a catalyst for meaningful clinical impact.
We welcome contributions that challenge assumptions, advance translational science, and ultimately improve patient care through responsible artificial intelligence.