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SkillsMP は awslabs/hcls-agent-skills から 40 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
収集済み skill 40 件中 40 件を表示しています。
Reasoning skill for healthcare revenue cycle denial management. Use when the user needs to appeal a claim denial, draft a payer-ready denial appeal letter, analyze a denial reason code, or determine whether a denied claim should be overturned, pended, or…
原文の言語: 英語
Reason about SaMD (Software as a Medical Device) regulatory compliance for FDA, EU MDR, and global submissions. Use when the user asks about IEC 62304 safety classification, ISO 14971 risk management, 21 CFR 820/QMSR quality system requirements, Design…
原文の言語: 英語
Reasoning skill for designing AWS GenAI and ML architectures for healthcare and life sciences workloads. Use when the user asks to choose between SageMaker and Bedrock, design a RAG system over medical literature, architect clinical NLP or medical imaging…
原文の言語: 英語
Reason about biomarker discovery and validation in HCLS — classifying biomarker intent, choosing feature-selection and cross-validation strategies, avoiding leakage, and planning external replication. Use when the user asks to discover, develop, or validate a…
原文の言語: 英語
Reason about CDISC SDTM and ADaM implementation for regulatory submissions. Use when the user asks about SDTM domain mapping, ADaM dataset design, controlled terminology versioning, define.xml completeness, FDA or PMDA submission requirements, query…
原文の言語: 英語
Generate code to assign cell type labels to single-cell RNA-seq clusters using CellTypist, SingleR, marker-based annotation, or reference label transfer (scANVI/ingest). Triggers on requests to "annotate cell types", "label clusters", "run CellTypist",…
原文の言語: 英語
Cheminformatics pipeline for small-molecule property calculation, filtering, and similarity analysis using RDKit. Use when the user asks to compute molecular descriptors, filter compounds by Lipinski or Veber rules, detect PAINS, calculate fingerprint…
原文の言語: 英語
Pipeline skill for healthcare claims data parsing, analysis, and fraud detection. Use when the user asks to parse X12 837 or 835 claim files, manipulate ICD-10 CPT or HCPCS codes, detect billing pattern anomalies, profile providers against specialty peers,…
原文の言語: 英語
Reasoning skill for healthcare claims billing rules and fraud detection logic. Use when the user asks about CMS billing rules, place of service codes, global surgery periods, modifier usage (25 59 76 77), NCCI edit logic, column 1 column 2 code pairs,…
原文の言語: 英語
Reason about clinical data terminology standards — MedDRA hierarchy (LLT→PT→HLT→HLGT→SOC), ICD-10 code structure and grouping, SNOMED CT concept model, LOINC panel relationships, and mapping decisions between systems. Use when the user asks to code adverse…
原文の言語: 英語
DICOM and NIfTI medical image processing pipeline. Triggers on DICOM, NIfTI, dcm2niix, de-identification, pydicom, DICOM header, conversion, anonymization, BIDS, DICOM tags, medical image format conversion, "DICOM to NIfTI", "burned-in PHI",…
原文の言語: 英語
Generate correct code for whole-slide image (WSI) analysis using TIAToolbox and foundation models (H-optimus-0, UNI, Prov-GigaPath). Triggers on requests involving whole-slide images, WSI, digital pathology, histopathology, SVS/NDPI/pyramidal TIFF, tissue…
原文の言語: 英語
Reason about drug repurposing strategies in HCLS — choosing between target-based and phenotype-based approaches, evaluating mechanism-of-action overlap, querying drug-gene interaction databases, assessing clinical translatability, and ranking candidates by…
原文の言語: 英語
Generate code for EDC export validation, clinical data range checks, cross-form consistency checks, SDTM structure validation, controlled terminology verification, and define.xml generation. Use when the user asks to validate clinical trial data exports,…
原文の言語: 英語
Parse and extract clinical data from HL7v2 messages and FHIR R4 resources using Python. Use when the user mentions HL7v2, HL7, FHIR, PID segment, OBX segment, MSH segment, Patient resource, Observation resource, Condition resource, MedicationRequest, EHR data…
原文の言語: 英語
Reason about germline and somatic variant classification using ACMG/AMP 2015 and AMP/ASCO/CAP frameworks. Use when the user asks to classify a variant, interpret a VCF annotation, resolve a VUS, apply ACMG criteria, weigh ClinVar evidence, evaluate gnomAD…
原文の言語: 英語
Reasoning skill for HEDIS measure specification, enrollment logic, exclusion evaluation, NCQA audit requirements, and care gap prioritization. Use when the user asks about HEDIS measure definitions, denominator/numerator/exclusion logic, continuous enrollment…
原文の言語: 英語
Reasoning skill for medical imaging study design and biomarker selection. Use when the user asks to plan an imaging study, choose a preprocessing strategy, select an imaging biomarker, design a radiomics pipeline, handle DICOM de-identification, plan…
原文の言語: 英語
Reason about ML experiment design for healthcare and life sciences data. Use when the user asks to design an ML study, choose a model for clinical/biomedical data, set up cross-validation, pick evaluation metrics, audit fairness, plan a regulatory submission,…
原文の言語: 英語
Molecular docking pipeline using AutoDock Vina for structure-based drug discovery. Triggers on docking, AutoDock Vina, receptor preparation, ligand preparation, PDBQT, grid box, virtual screening, binding affinity, pose prediction, structure-based virtual…
原文の言語: 英語
Reasoning skill for multi-omics data integration strategy selection. Use when the user asks to integrate transcriptomics with proteomics, combine multi-omic layers, choose between early intermediate or late integration, apply batch correction across omics,…
原文の言語: 英語
Pipeline skill for multi-omics data processing and integration. Use when the user asks to map gene IDs between HGNC Ensembl and UniProt, convert between omic data formats, run batch correction with ComBat or ComBat-seq, perform GSEA or over-representation…
原文の言語: 英語
NGS quality control pipeline for short-read sequencing data. Triggers on FastQC, QC, quality control, adapter trimming, coverage, mosdepth, Picard metrics, fastp, MultiQC, sequencing QC, BAM QC, WGS/WES coverage analysis.
原文の言語: 英語
Reasoning skill for prior authorization clinical policy evaluation. Use when the user asks about payer clinical criteria, step therapy requirements, medical necessity definitions, CMS LCD/NCD coverage rules, appeals documentation strategy, formulary tier…
原文の言語: 英語
Pipeline skill for automating prior authorization decision workflows. Use when the user asks to parse PA request data (X12 278 or FHIR PAS bundles), extract clinical features for adjudication, build rules-based PA decision engines, train ML classifiers on…
原文の言語: 英語
Reason about pharmacoepidemiologic study design for causal inference from real-world data — choosing active comparator new-user designs, emulating target trials, avoiding immortal time bias, handling time-varying confounding with marginal structural models,…
原文の言語: 英語
Pipeline skill for protein structure analysis covering PDB/mmCIF parsing, RMSD superposition, Ramachandran/dihedral analysis, binding pocket detection, contact maps, B-factor flexibility, DSSP secondary structure, and format conversion. Triggers on PDB,…
原文の言語: 英語
Pipeline skill for computing HEDIS quality measures from claims and clinical data. Use when the user asks to calculate HEDIS measure rates, check continuous enrollment, build denominator/numerator logic, detect care gaps, compute utilization rates, identify…
原文の言語: 英語
Reason about quantitative proteomics experiment design and data analysis strategy. Use when the user asks to choose between LFQ, TMT, and DIA quantification; select an imputation method for missing values; pick a normalization strategy; interpret differential…
原文の言語: 英語
Structural MRI/CT preprocessing pipeline for radiology workflows covering skull stripping, bias field correction, registration, and intensity normalization. Triggers on skull stripping, bias correction, registration, ANTs, FSL, HD-BET, N4, brain extraction,…
原文の言語: 英語
Pipeline skill for CMS-HCC risk adjustment calculation and coding gap identification. Use when the user asks to apply the ICD-10-to-HCC crosswalk, calculate RAF scores, resolve disease hierarchies programmatically, identify coding gaps from Rx or lab proxies,…
原文の言語: 英語
Reasoning skill for CMS-HCC risk adjustment strategy and methodology. Use when the user asks about CMS-HCC model versions V24 or V28, blended transition methodology, ICD-10-to-HCC mapping logic, disease interaction hierarchies, RAF score methodology, risk…
原文の言語: 英語
Reasoning skill for clinical risk stratification index selection and interpretation. Use when the user asks about LACE scores, Charlson Comorbidity Index, Elixhauser Index, readmission risk scoring, comorbidity weighting, SDOH Z-codes, Area Deprivation Index,…
原文の言語: 英語
Bulk RNA-seq analysis pipeline covering alignment (STAR), quantification (Salmon, featureCounts), and differential expression (DESeq2). Triggers on RNA-seq, STAR, Salmon, DESeq2, differential expression, gene expression, tximport, featureCounts,…
原文の言語: 英語
Real-world data cohort analysis pipeline for claims and EHR data — cohort identification with ICD-10, NDC, and CPT codes, medication adherence metrics (PDC/MPR), propensity score estimation and balance diagnostics, Kaplan-Meier survival curves, and Cox…
原文の言語: 英語
Scanpy-based single-cell RNA-seq analysis pipeline covering loading (10X, h5ad), QC, normalization, HVG selection, PCA/UMAP, Leiden clustering, differential expression, and batch correction (Harmony, scVI). Use when the user mentions single-cell, scRNA-seq,…
原文の言語: 英語
Reasoning skill for structure-based drug design strategy. Use when the user asks to assess target druggability, choose a docking strategy, select a scoring function, define a binding site, interpret docking results, plan molecular dynamics or free energy…
原文の言語: 英語
Single-cell trajectory inference pipeline covering diffusion pseudotime (DPT), PAGA, RNA velocity with scVelo, and fate mapping with CellRank. Use when the user mentions pseudotime, trajectory, lineage, differentiation, RNA velocity, scVelo, CellRank, PAGA,…
原文の言語: 英語
Reason about translational research problems in HCLS — especially neurology and hypothesis validation. Use when the user asks to design a validation study, evaluate a target, qualify a biomarker, choose endpoints, critique a preclinical-to-clinical plan, pick…
原文の言語: 英語
Germline and somatic short-variant calling pipeline for Illumina short-read data. Use when the user mentions BWA, BWA-MEM2, GATK, HaplotypeCaller, Mutect2, VCF, GVCF, VQSR, variant calling, germline, somatic, SNV, or indel calling from FASTQ/BAM.
原文の言語: 英語