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health_and_safety

Healthcare

About Healthcare

The Healthcare domain addresses critical areas like electronic medical records (EMR), patient safety, data privacy, and regulatory compliance. For instance, the `healthcare-phi-compliance` Skill enables AI Agents to process Protected Health Information (PHI) while adhering to stringent regulations. These tools empower healthcare professionals to enhance clinical decision-making and ensure robust data security.

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All Healthcare Skills

27 / 27 skills
food-safety

mfds-food-safety

by @nomadamas

An interview-based food safety check skill that queries public data from MFDS/Food Safety Korea. Before providing information, it asks about symptoms and consumption, and advises on emergency medical care for red flag situations, prioritizing user safety.

4.5(120)
6.4K
drug-safety

mfds-drug-safety

by @nomadamas

An interview-based drug safety check skill that queries the Korea Ministry of Food and Drug Safety (MFDS) public OpenAPI via k-skill-proxy, proactively asking about user symptoms and medication status before providing safer drug advice.

4.5(120)
6.4K
healthcare-compliance

healthcare-phi-compliance

by @affaan-m

Medical data privacy compliance mode, applicable to regulations like HIPAA, DISHA, GDPR, covering protection strategies for patient data, clinical data, and financial data.

4.4(20)
4.7K
emr

healthcare-emr-patterns

by @affaan-m

Electronic Medical Record and Electronic Health Record system development pattern library, prioritizing patient safety, clinical accuracy, and practitioner efficiency, covering patient intake workflow best practices.

4.4(21)
4.6K
cdss

healthcare-cdss-patterns

by @affaan-m

Clinical Decision Support System development patterns, integrated into EMR workflows, implementing patient safety critical functions like drug interaction checks, dosage verification engines, with zero tolerance for false negatives.

4.4(20)
4.5K
patient-safety

healthcare-eval-harness

by @affaan-m

Automated validation system for medical application deployment, where a single critical failure blocks deployment, ensuring non-negotiable patient safety, supporting Jest and other testing framework adaptations.

4.4(20)
4.5K
hipaa

hipaa-compliance

by @affaan-m

HIPAA compliance entry point for US healthcare compliance tasks, relying on healthcare-phi-compliance for PHI/PII processing, data classification, and audit logs.

4.4(3)
4.2K
clinical-asr

digital-health-clinical-asr-setup

by @nvidia

This skill bootstraps Stage 1 of the Clinical ASR Flywheel: verifies the NVIDIA API key, installs Python dependencies, and runs a TTS+ASR smoke test to ensure hosted speech stack accessibility. It clears the user for subsequent stages by proving end-to-end connectivity with clinical sentences.

4.3(120)
1.9K
clinical-asr

digital-health-clinical-asr-build

by @nvidia

This skill builds clinical ASR benchmarks by curating medical terms, tagging IPA pronunciations, and synthesizing audio into NeMo manifest format. It guides clinicians through term selection and pronunciation verification, enabling accurate evaluation of medical speech recognition systems.

4.3(120)
1.9K
asr-evaluation

digital-health-clinical-asr-eval

by @nvidia

This skill performs Stage 3 of clinical ASR evaluation: it transcribes a NeMo-format manifest via a chosen ASR NIM, scores four metrics (WER/CER/KER/SER), produces a five-section KER leaderboard with by-ipa_source diagnostics, and applies a decision tree to recommend next steps (fine-tune, rebuild, or pause). It helps teams pinpoint clinically dangerous term recognition failures and pronunciation coverage gaps. Ideal for validating ASR performance on medical terminology before deployment.

4.3(120)
1.9K
dicom

dicom-metadata-extract

by @nvidia

Extracts selected metadata from a single DICOM file and flags standard-tag Protected Health Information (PHI) presence, aiding medical data compliance reviews and preliminary screening. Provides standardized JSON metadata output for downstream processing. Not intended for anonymization or clinical use.

4.3(120)
1.9K
dicom

dicom-series-preflight

by @nvidia

Used for header-only preflight of a single DICOM series folder before conversion or inference. It automatically scans and outputs a JSON report with inventory, orientation axcodes, PHI flags, findings, and a verdict, helping medical AI developers validate DICOM data quality efficiently and avoid failures from anomalous data.

4.3(120)
1.9K
dicom

dicom-series-to-volume

by @nvidia

This Skill converts a CT DICOM series folder to a Hounsfield Unit NIfTI volume with affine evidence. It automatically applies rescale slope/intercept and builds orientation/spacing matrices, ideal for medical imaging preprocessing and segmentation pipeline inputs, saving time and reducing manual conversion errors.

4.3(120)
1.9K
mri

nv-generate-mr-brain

by @nvidia

This skill generates synthetic brain MRI volumes by wrapping the NVIDIA NV-Generate-CTMR workflow. It automatically stages configuration overrides, runs diffusion sampling, and outputs NIfTI volumes. Ideal for medical imaging research, algorithm validation, and education, it eliminates the need for custom inference code and reduces the complexity of generating synthetic data.

4.3(120)
1.8K
medical-imaging

nv-segment-ct

by @nvidia

This skill runs NV-Segment-CT VISTA3D on CT NIfTI volumes for automatic segmentation, producing label maps and result JSON. It wraps the official model and environment dependencies, streamlining medical image segmentation for research or pre-clinical evaluation scenarios.

4.3(120)
1.8K
synthetic-ct

nv-generate-ct-rflow

by @nvidia

Generates synthetic CT volumes and masks via the NV-Generate-CTMR rectified-flow pipeline, enabling medical AI teams to quickly produce diverse synthetic CT images and labels without real patient data, for model training and validation.

4.3(120)
1.8K
vae

nv-generate-vae-finetune

by @nvidia

Fine-tune the NV-Generate-CTMR MAISI VAE/autoencoder on user-supplied CT or MRI NIfTI training volumes. Automatically stages configuration, datalists, and exposes key hyperparameters via CLI. Supports preflight mode to validate data integrity before GPU training. Outputs fine-tuned checkpoints, enabling customized medical image generation model development.

4.3(120)
1.8K
medical-imaging

nv-segment-ctmr

by @nvidia

Automatically segments CT or MRI NIfTI volumes, producing label maps and evidence JSON. Designed for medical imaging analysis, it reduces manual annotation time and improves segmentation consistency.

4.3(120)
1.8K
ct-segmentation

nv-segment-ct-finetune

by @nvidia

Used for smoke testing or dataset finetuning of NV-Segment-CT VISTA3D on CT NIfTI labels, enabling researchers to quickly verify model compatibility or perform fine-grained training for specific anatomies, improving medical image segmentation accuracy.

4.3(120)
1.8K
legal-compliance

ra-qm-skills

by @alirezarezvani

Provides 12 production-ready Regulatory Affairs and Quality Management skills for HealthTech and MedTech organizations, ensuring compliance and quality standards.

4.3(20)
1.7K
risk-management

risk-management-specialist

by @alirezarezvani

Specializes in ISO 14971:2019 risk management implementation throughout the medical device lifecycle, providing planning and workflows.

4.2(20)
861
qms

quality-manager-qms-iso13485

by @alirezarezvani

Focuses on ISO 13485:2016 Quality Management Systems, providing implementation, maintenance, and certification support for medical device organizations to ensure product quality and regulatory compliance.

4.2(20)
784
medical-imaging

medical-imaging-review

by @luwill

Medical imaging AI literature review writing tool. Provides structured 7-phase workflow covering coronary CT, lung imaging, brain MRI, cardiac imaging, pathology, and retinal domains. Includes Zotero integration and quality checklists.

4.2(20)
689
clinical-reporting

clinical-reports

by @davila7

Writes clinical reports, ensuring medical information is precise, accurate, and compliant with regulatory standards. An AI Agent Skill to enhance work efficiency and automation.

4.2(20)
674
tcm

nihaixia-tcm-wiki

by @xiaojian94xiaojian

A classical formula TCM knowledge base based on Ni Haixia's Renji series (Acupuncture, Neijing, Shennong Bencao, Shanghan, Jingui). It can directly call Claude Code to answer questions on six-meridian pattern differentiation, formulas, acupoints, and medical cases. The system is organized according to Karpathy Wiki methodology, ensuring all answers are verified against the original text. Suitable for TCM learners and practitioners to quickly look up Ni's classical formula system, avoiding second-hand information bias.

4.0(20)
24
meta-analysis

meta-analysis-skill

by @Lokenqaq111

Run pairwise and network meta-analysis in R, supporting continuous, binary, prevalence, generic effect size, and NMA data. Suitable for rehabilitation and exercise science researchers to use extracted numeric CSV data for validation, synthesis, plotting, diagnostics, and generating reproducible Markdown reports; it does not handle literature searching, PDF numeric extraction, or automated GRADE/CINeMA rating.

4.0(20)
8
psychological-support

psychological-support-skill

by @a275857760

Provide warm and sincere psychological support, using the three levels of the mirror (illuminate → lighten → give) to help users recognize emotions, discover value, and give care. Suitable for scenarios such as anxiety, low mood, and self-denial. Use 'I' instead of AI identity in conversations, avoid clichés, and be warm but not excessive.

4.0(20)
1
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