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. We 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. We encourage submissions that not only highlight novelty but also demonstrate tangible, reproducible and ethical impact.

Accepted manuscript types: Research Articles, Brief Reports, Translational Science Case Studies. Other manuscript types may be considered with prior approval (direct questions to jcts@cambridge.org).

Mission alignment: The proposed thematic issue directly advances the Journal of Clinical and Translational Science mission to disseminate high-quality, impactful research that accelerates the translation of discoveries into improved health.

AI has emerged as a transformative force in clinical and translational science, with the potential to improve trial efficiency, enhance data quality, enable precision medicine, and address health equity. However, this potential will only be realized through rigorous, evidence-based applications—precisely the focus of this thematic issue.

By explicitly requiring data-rich manuscripts that present validated and transparent methods, real-world implementation, measurable impact, and broader reflections on sustainability, scalability, and generalizability, this collection will uphold JCTS’s commitment to scientific rigor, reproducibility, and transparency. Equally important, by welcoming studies that show negative results or lessons learned from failed implementations, the issue reinforces JCTS’s role in publishing knowledge that improves future research practice, even when outcomes do not meet expectations.

The emphasis on approach plus impact ensures that articles will advance both the science and the operational practice of clinical research, addressing priorities repeatedly emphasized in JCTS editorials:

• Promoting methodological innovation that is grounded in evidence.
• Encouraging cross-disciplinary team science that integrates data science, informatics, and clinical expertise.
• Supporting equitable, reproducible, and efficient translational processes across the full continuum of research.

This thematic issue will serve as a curated, authoritative resource for the translational science community, providing tested AI solutions and cautionary examples that inform best practices and accelerate the pace of discovery-to-impact translation.

 

Submission Guidelines

• Deadline for Submission: July 13, 2026
• Manuscripts should be submitted online via the Journal’s ScholarOne submission site.
• When submitting your manuscript, please select “Artificial Intelligence in Action” in response to the Thematic Issue submission question.

For detailed information on each manuscript category and submission guidelines, please visit the JCTS Instructions for Contributors on Cambridge Core.

Open Access and Fees

JCTS is a fully Gold Open Access journal. Information on the Journal’s Open Access policies, including the current Article Processing Charge (APC), can be found here. Standard APCs will apply for thematic issue submissions unless other arrangements have been made in advance with the publisher.

Contact Information

Questions regarding this themed issue should be directed to the editors listed below via the JCTS Editorial Office at jcts@cambridge.org.

Lead editor:

Julio C. Facelli, PhD

Guest editors: 

Abu Mosa

Mei Liu

Gina-Maria Pomann