Launch Editorial of AI in Medicine

Distinguished colleagues in the global medical and AI communities,

As artificial intelligence reshapes the boundaries of human knowledge, medicine stands at the threshold of its most profound transformation since the advent of evidence-based practice, moving from intuition-guided clinical judgment to a model co-driven by data and intelligence and advancing from population-level statistical inference to precision, patient-specific optimization. This transformation is already tangible in every dimension of the clinical enterprise: Deep learning is achieving clinician-level performance in disease detection, diagnosis, prediction, and treatment from oncology to cardiology [1]. AI is redefining the sensitivity and throughput of medical image analysis, spanning radiological screening, digital pathology, and multimodal imaging [2]. Clinical decision support systems are synthesizing heterogeneous patient data from laboratory values, vital signs, and clinical notes to deliver high diagnostic and prognostic accuracy at the bedside [3]. Natural language processing unlocks actionable insight from unstructured electronic health records, transforming medical informatics and enabling medical data processing at unprecedented scales [4]. In genomics and precision medicine, multi-omics integration enables patient-specific therapeutic strategies tailored to individual biology [5], whereas AI-guided drug discovery and development pipelines, including clinical trial design and recruitment, are compressing timelines from years to months [6]. Intelligent devices and instruments are embedding diagnostic intelligence at the point of care; remote monitoring and telemedicine are expanding access to expertise across geographic and socioeconomic boundaries; AI-driven rehabilitation and assistive technologies are opening new pathways to recovery for patients with chronic disease and disability [7]. However, these advances bring formidable responsibilities: many systems remain opaque “black boxes” that limit clinician trust, dataset biases threaten equitable performance across diverse populations [8], and AI-driven diagnostics and patient care pose ethical challenges. To advance rigorous, reproducible, and responsible research across this full spectrum, AI in Medicine is launched today as an international open-access journal dedicated to artificial intelligence and computer science techniques applied to medicine, guided always by the foundational principle of our profession: first, do no harm.