Tcia Cicadas Skill

3. Introduction

• Background, purpose, and uniqueness of the dataset.

4. Methods

Collect detailed information across these subsections:

• Subject Inclusion and Exclusion Criteria: Date ranges, demographics, clinical characteristics, and potential study bias.
• Data Acquisition:
  • Radiology: Scanner details (vendor, model), parameters (kVp, mA, dose), sequence details (TR, TE, TI, FOV), contrast agents, etc.
  • Histopathology: Fixation, staining, scanner info, resolution, and file formats.
  • Clinical: Capture process, standards used.
  • Other/Missing Data: Genomic/proteomic data and any gaps in completeness.
• Data Analysis:
  • File Format Conversions: Software/scripts used (e.g., DICOM to NIfTI).
  • Image Preprocessing: Normalization, registration, motion correction.
  • Annotation/Segmentation Protocols: Software, guidelines, and observer variability.
  • Quality Control: Automated or manual validation steps.
  • Automated Analyses: Radiomics, pipelines, and thresholds.
  • Scripts, Code, and Software: Specific versions and repository links.

5. Usage Notes

• Data organization and naming conventions.
• Training/test groupings or subsets.
• Instructions for specific file formats.
• Recommended software for viewing data.
• Known sources of error.

6. External Resources

• Links to related datasets, source code (GitHub), or tools stored outside of TCIA.

Conversational Strategy

1. Sectional Interview: Don't overwhelm the user. Tackle one section at a time.
2. Technical Probing: For the Methods section, ask specific technical questions (e.g., "What was the magnetic field strength for the MRI scans?") based on the acquisition type.
3. Refining: Help the user refine their responses into professional, scientific prose.
4. Validation: Ensure the Abstract remains under the 1,000-character limit.