clinical-skills

Integrate AI detection into PACS workflow. Also use when setting up, configuring, or optimizing AI detection systems for medical imaging. Also covers Aidoc, Nvidia Clara, Zebra Medical, MaxQ AI, and Qure AI integration.

QA AI outputs, detect false positives/negatives, and validate AI results. Also use when evaluating AI system performance, reviewing AI-assisted findings, or conducting quality assurance on AI detection and reporting tools.

Guidance for AI-assisted structured reporting tools. Also use when the user mentions AI reporting, automated templating, speech-to-report, or wants to configure or optimize AI-assisted radiology reporting systems (RadAI, Abba, DeepRad).

Use LLM APIs for radiology tasks. Also use when integrating medical LLMs (MedPaLM, MedLM, Google Health, Amazon HealthLake) for report analysis, clinical reasoning, or radiology AI workflows.

Assesses medical image quality against clinical standards and identifies optimization opportunities. Use when user mentions "image quality audit", "artifact review", "dose analysis", "protocol deviation", "quality metrics", "diagnostic adequacy", or "technique optimization".

Retrieves and analyzes operational metrics from radiology information systems. Use when user mentions "radiology KPIs", "productivity metrics", "turnaround time analysis", "workload distribution", or needs operational analytics.

Monitors and improves radiology report quality through systematic audit and feedback. Use when user mentions "report quality review", "discrepancy audit", "report completeness", "addendum analysis", or needs quality assurance.

Performs comprehensive review of imaging studies for clinical, QA, tumor board, or comparison purposes. Use when user mentions "review this study", "comprehensive review", "tumor board preparation", "compare with priors", or needs structured imaging analysis.

Analyze structured/free-text radiology reports, extract key findings, measurements, and impressions. Also use when the user provides a report for review, summary, data extraction, critical findings identification, or report quality assessment. For structured reporting templates, see structured-reporting.

Create and optimize structured radiology reports using standardized templates. Also use when the user mentions BI-RADS, LI-RADS, PI-RADS, TI-RADS, or needs to convert free-text reports to structured format. For free-text analysis, see radiology-report-analysis.

Auto-detect imaging modality (CT, MRI, X-ray, US, etc.) from user input, DICOM file headers, or file analysis. Also use when the user mentions "what modality", "detect from file", "identify imaging type", or needs to classify imaging studies. For PACS queries, see pacs-workflow.

Establish and manage user's clinical radiology environment configuration - PACS, EHR, modality types, AI tools, and workflow settings. Also use when setting up or updating radiology workflow context, configuring PACS connections, or managing clinical environment settings.

Provides preprocessing pipelines and techniques for radiology datasets used in AI development. Use when user mentions "preprocess radiology data", "DICOM preprocessing", "image normalization", "data augmentation", or needs to prepare datasets.

Designs and executes validation studies for radiology AI models to ensure clinical reliability and regulatory compliance. Use when user mentions "validate model performance", "external validation", "statistical analysis", "clinical validation", or needs model evaluation.

Guides researchers and developers through radiology dataset selection, access, and utilization for AI development. Use when user mentions "radiology dataset", "medical imaging data", "RSNA challenge", "MIMIC data access", or needs dataset guidance.

Create patient education materials for imaging procedures and findings. Also use when developing handouts, FAQs, or educational content about radiology procedures, preparation, or conditions found on imaging.

Generate patient-friendly radiology result communications in plain language. Also use when the user needs to explain findings to patients without medical jargon, write result letters, or create follow-up reminders.

Query and retrieve DICOM objects via DICOMweb REST API. Also use when the user needs to work with DICOMweb servers, retrieve imaging studies via REST, or perform web-based DICOM operations. For traditional DICOM queries, see pacs-workflow.

Query PACS, retrieve studies, manage worklists, and integrate with PACS workflows. Also use when the user needs to interact with picture archiving systems, search for imaging studies, retrieve DICOM data, or manage radiologist worklists. For DICOMweb REST queries, see dicom-web-query.

Evidence-based literature search for radiology. Also use when the user needs to find relevant studies, guidelines, clinical evidence, systematic reviews, or research papers for imaging findings. For guideline-specific searches, see guideline-integration.

Links current findings to priors, related literature, and correlated data. Use when user mentions "compare to priors", "find prior studies", "correlate with", "longitudinal comparison", or needs historical context.

Access and apply professional radiology society guidelines. Use when user mentions "ACR criteria", "appropriateness rating", "guideline for", "society recommendation", "BI-RADS update", "dose reference levels", or "protocol guidelines".

Access and synthesize medical imaging research literature. Use when user mentions "recent research on", "literature review", "published studies", "evidence for", or needs to find relevant research.

Ensure recommended imaging is completed and close care gaps in radiology. Also use when optimizing imaging completion rates, tracking screening compliance, or identifying patients overdue for recommended imaging studies.

Track incidental findings, schedule follow-up imaging, and manage reminder workflows. Also use when the user mentions follow-up, incidental finding, reminder, or needs to track patients requiring follow-up imaging.

Create, optimize, and manage imaging referrals between providers. Also use when the user needs to improve referral quality, add relevant clinical information, or track referral status. For clinical decision support, see guideline-integration.

Integrate AI detection into PACS workflow. Also use when setting up, configuring, or optimizing AI detection systems for medical imaging. Also covers Aidoc, Nvidia Clara, Zebra Medical, MaxQ AI, and Qure AI integration.

QA AI outputs, detect false positives/negatives, and validate AI results. Also use when evaluating AI system performance, reviewing AI-assisted findings, or conducting quality assurance on AI detection and reporting tools.

Guidance for AI-assisted structured reporting tools. Also use when the user mentions AI reporting, automated templating, speech-to-report, or wants to configure or optimize AI-assisted radiology reporting systems (RadAI, Abba, DeepRad).

Ensure recommended imaging is completed and close care gaps in radiology. Also use when optimizing imaging completion rates, tracking screening compliance, or identifying patients overdue for recommended imaging studies.

Links current findings to priors, related literature, and correlated data. Use when user mentions "compare to priors", "find prior studies", "correlate with", "longitudinal comparison", or needs historical context.

Provides preprocessing pipelines and techniques for radiology datasets used in AI development. Use when user mentions "preprocess radiology data", "DICOM preprocessing", "image normalization", "data augmentation", or needs to prepare datasets.

Query and retrieve DICOM objects via DICOMweb REST API. Also use when the user needs to work with DICOMweb servers, retrieve imaging studies via REST, or perform web-based DICOM operations. For traditional DICOM queries, see pacs-workflow.

Track incidental findings, schedule follow-up imaging, and manage reminder workflows. Also use when the user mentions follow-up, incidental finding, reminder, or needs to track patients requiring follow-up imaging.

Access and apply professional radiology society guidelines. Use when user mentions "ACR criteria", "appropriateness rating", "guideline for", "society recommendation", "BI-RADS update", "dose reference levels", or "protocol guidelines".

Assesses medical image quality against clinical standards and identifies optimization opportunities. Use when user mentions "image quality audit", "artifact review", "dose analysis", "protocol deviation", "quality metrics", "diagnostic adequacy", or "technique optimization".

Create, optimize, and manage imaging referrals between providers. Also use when the user needs to improve referral quality, add relevant clinical information, or track referral status. For clinical decision support, see guideline-integration.

Performs comprehensive review of imaging studies for clinical, QA, tumor board, or comparison purposes. Use when user mentions "review this study", "comprehensive review", "tumor board preparation", "compare with priors", or needs structured imaging analysis.

Use LLM APIs for radiology tasks. Also use when integrating medical LLMs (MedPaLM, MedLM, Google Health, Amazon HealthLake) for report analysis, clinical reasoning, or radiology AI workflows.

Auto-detect imaging modality (CT, MRI, X-ray, US, etc.) from user input, DICOM file headers, or file analysis. Also use when the user mentions "what modality", "detect from file", "identify imaging type", or needs to classify imaging studies. For PACS queries, see pacs-workflow.