Scope and Focus

JRAI publishes original research, technical notes, and reviews that bridge robotics engineering and clinical practice. We seek evidence driven work that improves surgical precision, patient safety, and intelligent decision support.

Interdisciplinary teams are encouraged to submit studies that combine algorithm development with clinical validation, simulation testing, or real world deployment results.

Topics of Interest

We welcome submissions across the full pipeline of intelligent surgical systems and applied robotics.

• Robotic assisted surgery and teleoperation systems
• Medical imaging, computer vision, and surgical navigation
• Machine learning for diagnostics, triage, and outcomes prediction
• Autonomous systems, safety control, and human robot interaction
• AI enabled rehabilitation devices and assistive robotics
• Clinical validation, benchmarking, and regulatory readiness
• Data governance, bias mitigation, and ethical AI in healthcare

Submission Readiness

Prepare a structured abstract, clear methodology, and validation metrics aligned to the clinical or engineering objective. Include data availability statements and ethical approvals where applicable.

• Confirm scope alignment with robotics or AI in healthcare
• Provide performance benchmarks and limitations
• Include ethics, consent, or safety approvals if needed

Research Visibility

Open access publication ensures that robotic surgery and AI research is available to engineers, clinicians, and health system leaders worldwide.

Quality Assurance

Every manuscript receives editorial screening and independent review to protect the integrity of technical and clinical claims.

Special Themes

We welcome proposals for thematic clusters on topics such as autonomous surgery, AI assisted imaging, and safety validation. Indicate thematic alignment in your cover letter for priority consideration.

Data and Code Transparency

Where possible, provide datasets or code repositories to support reproducibility. Clear documentation helps reviewers assess deployment readiness.

Industry Collaboration

Submissions from industry and clinical collaborations are encouraged when reporting standards and conflict disclosures are clear.

Interdisciplinary Collaboration

We value manuscripts that unite engineering innovation with clinical implementation. Highlight how your team integrates robotics, AI, and clinical expertise to solve real surgical challenges.

Evaluation and Benchmarks

Provide clear evaluation metrics, baseline comparisons, and validation protocols. Strong benchmarking strengthens confidence in algorithm performance and system safety.

Clinical Translation

Explain how the proposed system or model could be adopted in clinical workflows. Translational insight helps reviewers assess real world relevance.

Ethics and Safety

Address patient privacy, safety controls, and ethical considerations for autonomous or AI assisted systems. Ethical clarity improves trust and adoption.

Early Career Authors

JRAI welcomes submissions from early career researchers and graduate teams. Clear documentation and validation detail help establish credibility and visibility.

Submission Timeline

JRAI accepts submissions year round with rolling publication. Early submission helps align your work with upcoming themes and allows time for revisions.

Clinical Trials and Validation

If your study includes clinical trials or prospective validation, clearly describe study design, endpoints, and safety protocols. Transparency improves clinical confidence and review efficiency.

AI Transparency

Disclose model architecture, training data composition, and evaluation strategy. Explain limitations and generalizability to avoid overstatement of clinical performance.

Hardware and Device Reporting

For robotic systems, include hardware specifications, control parameters, and calibration details. Clear reporting helps readers understand system constraints and reproducibility.

Human Factors

Describe usability testing, workflow integration, and human robot interaction outcomes when relevant. These insights help bridge engineering innovation and clinical adoption.

Regulatory and Standards

If your work aligns with regulatory pathways or standards, include relevant references and compliance considerations. This strengthens the translational value of your submission.

Simulation and Training

Papers on simulation platforms, training systems, and digital twins are encouraged when they demonstrate measurable improvements in skill acquisition or system validation.

Dataset and Benchmark Papers

Dataset releases should include clear collection protocols, annotations, and usage constraints. Benchmark studies should explain baseline selection and evaluation criteria.

Collaborative Networks

We encourage multi site and cross disciplinary collaborations that demonstrate scalability, reproducibility, and real world deployment potential.

Submission Checklist

Include a clear statement of novelty, a reproducible evaluation plan, and a concise summary of clinical relevance. These elements help editors route your paper efficiently.

Peer Review Timeline

Submissions are reviewed on a rolling basis. Authors receive status updates throughout review and clear guidance on revisions when requested.

Clinical Imaging Quality

If your work relies on imaging data, describe acquisition protocols, preprocessing steps, and quality control measures. This detail improves interpretability and trust.

Responsible AI Governance

Discuss fairness, bias assessment, and transparency for AI assisted decision support. Responsible AI reporting supports clinician confidence and patient safety. Include explainability methods, monitoring plans for model drift, and safeguards for high risk decisions. Provide audit trail details where feasible so regulators and clinical partners can verify accountability. This clarity supports safe adoption and responsible deployment globally.