JCTS call for papers: how AI is advancing clinical and translational research

Artificial Intelligence in Action: Tested and Proven Approaches to Transforming Clinical and Translational Science

The Journal of Clinical and Translational Science (JCTS) invites submissions to this thematic issue highlighting rigorous studies that measure how artificial intelligence (AI) is advancing clinical and translational research and transforming the broader clinical and translational science (CTS) enterprise. They seek manuscripts that go beyond conceptual discussions to present:

• Validated AI approaches with clear methods, robust datasets, and measurable outcomes in clinical or translational contexts that improve the effectiveness, efficiency, generalizability, and reliability of clinical and translational research.
• Proven solutions for scaling the infrastructure and capabilities that enable AI tools.
• Evaluations of AI solutions in real-world settings, including studies of implementation, effectiveness, efficiency, quality, decision-making, resource allocation, or other CTS outcomes.
• Critical analyses of limitations, failures, or negative results where AI applications did not yield the intended benefit, with insights into causes and lessons learned—for example, thoughtful examination of root causes related to data quality, algorithmic bias, health disparities, generalizability, integration challenges, or contextual constraints—that can guide future efforts.
• Broader findings on trust, interpretability, transparency, sustainability, scalability, reproducibility and generalizability, including considerations of long-term maintenance, adaptability to different research contexts, interoperability, regulatory alignment, and strategies for ethical, equitable, and cost-effective deployment.
• Implementation of innovative scientific and research processes that leverage AI tools.
• Methods that measure and communicate AI uncertainties to the CTS enterprise.
• Innovative methods for continuous monitoring and adaptive learning to detect and mitigate performance drift, ensuring sustained accuracy, fairness, and reliability of AI systems over time.
• Evaluations of how AI impacts the translational science workforce, including the clinical partners in translational science.
• Scalable methods for evaluations of human–AI collaboration, including usability, researcher and participant engagement, and workflow integration.
• Engaging Patients and communities as critical collaborators throughout the development and implementation process  

Eligible AI domains include—but are not limited to—predictive modeling (e.g., risk stratification for precision clinical trials), unsupervised natural language processing (e.g., clinical information extraction without expert annotations for participant screening, outcomes ascertainment, or safety signals), computer vision (e.g., trial endpoints from medical imaging and digital pathology), causal inference (e.g., counterfactual modeling, target trial emulation), generative AI and AI agents (e.g., drafting research documentation, coding assistance, conversational agents for participants or researchers), reinforcement learning (e.g., adaptive treatment strategies and decision support), and multi-modal integration (e.g., extracting data, combining EHR, imaging, genomic, and other data sources).

Applications may span the full translational spectrum—from basic discovery and early algorithm development to clinical integration and population health impact, with priority for manuscripts that tackle a bottleneck in the translational pathway, including innovative AI approaches to trial design, tools and strategies to enhance participant recruitment and retention, methods and tools for data harmonization and interoperability, advanced decision support AI systems integrated into clinical workflows, and approaches for post-market surveillance.

Aligned with JCTS's mission to accelerate the translation of discoveries into improved health, this thematic issue will feature studies that pair technical innovation with scientific and clinical rigor. Submissions are encouraged that not only highlight novelty but also demonstrate tangible, reproducible and ethical impact.

Deadline for Submission: July 16, 2026

For more information and submission guidelines, visit cambridge.org/core/journals/journal-of-clinical-and-translational-science.