medical-imaging-review

Writing a systematic literature review for medical imaging AI research requires gathering papers from ArXiv and PubMed, then structuring the analysis. This Skill automates that process using a 7-phase workflow to collect sources and draft structured survey sections.

Structuring a survey paper on deep learning for CT lung nodule detection requires domain-specific templates covering datasets, methods, and clinical applications. This Skill provides these templates and guides the drafting process for medical imaging tasks like detection and segmentation.

Yes, you can use Zotero to manage references when generating a medical imaging AI survey. This Skill integrates directly with Zotero, alongside ArXiv and PubMed, to ensure broad literature collection and seamless reference management during the review process.

The best way to find deep learning papers on MRI segmentation for a systematic review is searching multi-source databases. This Skill leverages ArXiv, PubMed, and Zotero to execute comprehensive literature collection across various medical imaging domains and tasks.

Yes, the literature review generation process covers ultrasound and pathology imaging tasks. It provides domain-specific templates and structured guidance for writing systematic reviews across CT, MRI, X-ray, ultrasound, and pathology imaging modalities.