qinyan-topic-analysis

To generate a research proposal topic from literature search results, provide your scientific domain and query to perform evidence-based trend and gap analysis, yielding 3-5 differentiated candidate topics with cited references.

Finding research gaps in PubMed or ArXiv papers for a thesis proposal requires analyzing large-scale search results to identify evidence-based trends and blank areas, outputting topic directions, research value, and difficulty analysis with cited references.

Yes, you can use evidence-based topic analysis for grant writing across medical, humanities, and computer engineering fields to scope differentiated research directions and ensure feasibility with cited literature support.

The best way to avoid overly broad or narrow scientific writing topics is to apply evidence-based trend and gap analysis to real literature search results, ensuring your selected topic has differentiation, feasibility, and trend justification.

Yes, you need to provide your research domain and focus to initiate the Qinyan Academic OpenAPI-based paper search workflows, which then retrieves the large-scale literature required for generating topic recommendations.

Limitations of generating research topics from automated literature search include the strict requirement to base suggestions on real retrieved papers without fabricating trends, ensuring all 3-5 candidate topics maintain differentiation and feasibility.