Clinical AI Skills

Auto-detect imaging modality from input or files. Supports X-ray, CT, MRI, Ultrasound, and more.

Establish user's clinical environment, preferences, and workflow context for personalized assistance.

Query PACS servers and retrieve studies. Supports DICOM C-FIND, C-MOVE operations.

Evidence-based literature search via PubMed/MEDLINE API. Find relevant medical research.

REST queries to DICOMweb servers. QIDO-RS and WADO-RS support for cloud PACS.

AI-assisted structured reporting for radiology. Integration with RadAI, Abba, DeepRad.

Integrate AI detection into radiology workflow. Supports Aidoc, Nvidia Clara, Zebra, MaxQ, Qure.

Use LLM APIs for radiology tasks. MedPaLM, MedLM, Google Health, HealthLake integration.

QA AI outputs, detect errors and inconsistencies in AI-generated radiology reports.

Analyze structured and free-text radiology reports. Extract findings, impressions, and recommendations.

Generate BI-RADS, LI-RADS, PI-RADS structured reports with proper coding and templates.

Systematic review of imaging studies with standardized checklists and reporting templates.

Create and improve imaging referrals with appropriate modality selection and clinical indications.

Track incidental findings and schedule follow-ups. Manage recall reminders and compliance.

Ensure recommended imaging is completed. Identify and close care gaps in screening.

Generate patient-friendly result communications. Clear, empathetic imaging results letters.

Create procedure and condition education materials for patients. Simplify medical terminology.

Dashboard metrics - volume, TAT (turnaround time), accuracy, productivity analytics.

QC/QA review of imaging protocols. Assess image quality and protocol compliance.

Reporting accuracy review. Assess report quality, completeness, and clinical accuracy.

Apply ACR/ESR appropriateness criteria. Ensure imaging follows evidence-based guidelines.

Link findings to relevant literature and similar cases. Evidence-based correlation.

Medical imaging research literature search. Stay current with latest imaging research.

Guide to public radiology datasets. RSNA, MIMIC, CheXpert, and more.

Prepare DICOM/images for AI training. Normalization, augmentation, format conversion.

Validate AI model performance on radiology datasets. Metrics, ROC curves, confusion matrices.