By PhenoML
PhenoML skills for healthcare data processing: workflow creation, condition extraction, patient registration, and real-world evidence analysis
Create and execute PhenoML workflows for healthcare data processing, including condition creation from clinical notes and patient registration with deduplication
This skill provides real-world evidence (RWE) analysis using PhenoML APIs. It enables biopharma analysts to define patient cohorts, generate population statistics, compare cohorts, and assess study feasibility.
A collection of Claude Code plugins and skills that enable developers to rapidly build and test healthcare data workflows using PhenoML. These interactive skills provide guided, conversational experiences for using PhenoML APIs.
.claude/settings.json to ensure sensitive files can't be accessed (example provided in this repo)claude
/plugin marketplace add PhenoML/phenoml-skills
/plugin install phenoml-workflow@phenoml-skills
In the chat input, type / to open the command menu.
Select Manage Plugins
Click Marketplaces
Paste the repo URL: https://github.com/PhenoML/phenoml-skills
Click Install
PhenoML Skills will now appear in your Plugins list!
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npx claudepluginhub phenoml/phenoml-skills --plugin phenoml-workflowComprehensive FHIR software development skill covering FHIR R4/R5 APIs, resource modeling, server implementation, profile validation, terminology, SMART on FHIR, FSH authoring, SUSHI, GoFSH, and IG publishing
Claude for Healthcare — skills for payer, provider, pharma, and general healthcare work, with hosted MCP connections to CMS Coverage, ICD-10, NPI Registry, Clinical Trials, and PubMed.
Claude Code skill pack for OpenEvidence medical AI (24 skills)
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HealthCare domain specialization with HIPAA compliance, HL7 FHIR interoperability, PHI data handling, clinical data modeling, EHR system integration, medical device software (IEC 62304), telehealth architecture, and healthcare analytics.
Design experiments, profile datasets, build models, and audit them for bias before shipping
Implementation of the Dr. Ralph technique - continuous self-referential AI loops for interactive iterative development. Run Claude in a while-true loop with the same prompt until task completion.