Use AI responsibly across the research workflow
A focused AI learning area for literature review, writing support, data analysis, productivity, and responsible usage.
Learning topics in this section
Each topic is written for practical use, with emphasis on transparency, responsible authorship, accurate attribution, publication ethics, and open access publishing standards.
Guidance is prepared to support ethical publishing practice: clear journal information, transparent fees where applicable, responsible peer review, proper citation, licensing awareness, data integrity, and accountable AI use.
This AI section helps researchers use AI as a responsible support tool, not as a substitute for scholarly judgment. It focuses on privacy, verification, originality, citation accuracy, and disclosure where journal policy requires it.
What to focus on
- Use AI for planning, outlining, language improvement, checklist generation, and workflow support, while keeping analysis, interpretation, and final responsibility with the authors.
- Never paste confidential manuscripts, reviewer reports, patient data, unpublished datasets, or private institutional material into tools unless policy and permissions clearly allow it.
- Verify every source, citation, quote, statistic, and factual claim through trusted databases or original publications. AI-generated references may be inaccurate or fabricated.
- Follow the target journal policy for AI disclosure, authorship, image generation, data handling, and editorial transparency.
Readiness checklist
- No confidential data entered into AI tools
- All citations verified manually
- AI output checked by subject expert
- Original author analysis preserved
- Journal AI policy reviewed
- Disclosure prepared if required
AI Prompt Library
A structured prompt resource for literature discovery, outlining, editing, summarizing, and research planning with human verification.
AI Research Workflow
Shows where AI can support research tasks while preserving author responsibility, originality, confidentiality, and critical review.
AI Literature Review
Guidance for using AI to organize search terms and summaries while verifying sources through trusted databases.
AI Writing Assistance
Explains responsible use of AI for clarity, grammar, structure, and editing without replacing author analysis or originality.
AI for Data Analysis
Covers cautious AI support for code, interpretation, visualization, and documentation with expert validation of outputs.
Responsible AI Usage
Focuses on transparency, privacy, bias awareness, citation accuracy, journal policy compliance, and human accountability.
AI Productivity Tools
Introduces tools for organization, reading, drafting, reference support, and workflow management with quality checks.
AI Limitations
Explains hallucinations, fabricated citations, bias, data privacy risks, and why authors must verify all AI-assisted outputs.