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cccskills

「clinical」の検索結果

559 件 ・ 関連度順

概要と使いどころ

Apply the bioengineering, translational systems biology, and tissue modeling frameworks of Linda Griffith, Professor of Biological Engineering at MIT and tissue engineering pioneer. Use this skill whenever facing decisions, designs, or evaluations in bioengineering, tissue modeling, microphysiological systems (organs-on-chips), synthetic matrix design, disease subtyping, or drug target validation. Reach for this skill when evaluating preclinical models (human vs. animal), reframing overlooked or neglected pathologies into rigorous engineering challenges, selecting biomaterials, designing cell signal processing assays, or diagnosing operational flaws in experimental platforms (e.g., PDMS compound absorption or Matrigel lot variability).

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/mimeo2832026年9月3日 更新

Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-claude-plugin2382026年10月9日 更新

Clinical-trial readout analysis: pull the trial, evaluate the readout with AdCom-style scrutiny (endpoints, statistics, subgroups, missing data, safety, tolerability/persistence), place it in a cross-trial comparison lattice vs SoC and class peers, and size the stock reaction with historical grounding. The judgment core for binary biotech events.

日本語の概要は準備中です。原文の説明を表示しています。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Weekly clinical-trial status diff — the 11-category change report over the stored weekly snapshots (spec 055 FR-B03). Surfaces exactly what changed on the trial registry for your coverage: New / Suspended / Withdrawn / Terminated / Recruiting / Recruitment-Complete / Completed / Ahead / Delayed / Upsized / Downsized, every row carrying previous and new values, with risk flags on Terminated and Downsized and re-timing flags on Ahead and Delayed. The stored-previous-value discipline makes each week's diff reproducible.

日本語の概要は準備中です。原文の説明を表示しています。

agentii-ai/agentii-investment-intelligence2072026年9月29日 更新

Think and work like an expert Gene Therapy Scientist. Use when a task calls for Gene Therapy Scientist judgment. Reasons from vector biology, biodistribution, linked potency, and integration risk through ddPCR titer, empty/full analytics, ISA and off-target NGS (GUIDE-seq, CIRCLE-seq), and ICH S12 nonclinical design while treating pre-existing capsid neutralizing antibodies, RCV/RCA/RCR positivity, gonadal vector genome, and oligoclonal VCN expansion as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Dentist-Scientist. Use when a task calls for Dentist-Scientist judgment. Reasons from oral biofilm-host ecology, tissue healing capacity, and patient-level clinical endpoints (DMFS, PD/CAL, implant survival) through PICO/PROSPERO protocols, CAMBRA and 2017 AAP/EFP staging, ISO 4049/14801 bench tests with thermocycling, and GRADE-rated reviews while treating in-vitro-to-chairside leaps, plaque-index surrogates without caries reduction, and examiner calibration drift as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Think and work like an expert Comparative Medicine Researcher. Use when a task calls for Comparative Medicine Researcher judgment. Reasons from species biology, translational validity, and the 3Rs through model-validity frameworks, IACUC protocols, ARRIVE 2.0 reporting, and FELASA/AALAS health surveillance while treating substrain drift, subclinical colony infection (murine norovirus, pinworm, Mycoplasma), analgesia-pathway confounds, and unstated husbandry variables as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/scientific-agents2052026年10月3日 更新

Computes and interprets treatment effect measures (OR, RR, RD, HR, NNT) with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen, MOVER, profile likelihood, Bender NNT) and reports marginal vs conditional estimands per FDA 2023 covariate adjustment guidance. Use when reporting treatment effects in confirmatory trials, comparing effect sizes across studies, or constructing forest plots.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Resolves rsIDs, navigates RsMergeArch/SNPHistory merge chains, and converts between rsID, SPDI, HGVS, and VCF representations using the dbSNP Build 156 JSON architecture. Use when normalizing variant identifiers, joining variant databases by cluster ID, or tracking deprecated rsIDs through historical merges.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Build weighted gene co-expression networks to identify modules of co-regulated genes and relate them to phenotypes using WGCNA and CEMiTool. Detects hub genes and module-trait relationships from bulk or single-cell expression data. Use when finding co-expression modules, identifying hub genes, or relating gene networks to clinical or experimental variables.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Deep learning-based variant calling from long reads using Clair3 for SNPs and small indels. Use when calling germline variants from ONT or PacBio alignments, particularly when high accuracy is needed for clinical or research applications.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Calculates species richness, diversity, and turnover using the Hill number framework with iNEXT coverage-based rarefaction/extrapolation, asymptotic diversity estimation, and beta diversity partitioning (betapart turnover vs nestedness). Compares assemblages using coverage-standardized rather than size-standardized rarefaction. Use when quantifying biodiversity from species abundance or incidence data, comparing diversity across sites, or constructing rarefaction curves. Not for clinical 16S microbiome alpha/beta diversity (see microbiome/diversity-analysis).

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Detect antimicrobial resistance genes using AMRFinderPlus, ResFinder, and CARD. Screen isolates and metagenomes for resistance determinants. Use when characterizing resistance profiles in clinical isolates, surveillance samples, or metagenomic data.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Analyzes time-to-event data using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression with lifelines. Builds survival models from clinical and omics features. Use when predicting patient survival or modeling time-to-event outcomes.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Applies ACMG/AMP 2015 framework with ClinGen SVI specifications, Tavtigian 2018/2020 Bayesian point system, Abou Tayoun 2018 PVS1 decision tree, Pejaver 2022 calibrated PP3/BP4 thresholds for REVEL/BayesDel/AlphaMissense, Brnich 2020 PS3/BS3 OddsPath, Walker 2023 SpliceAI splicing framework, and AMP/ASCO/CAP 2017 tumor tiers. Use when classifying germline variants P / LP / VUS / LB / B, applying VCEP-specific CSpec rules, computing Whiffin BS1, or assigning cancer Tier I-IV per Li 2017.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

End-to-end EHR predictive modeling pipeline with PyHealth, covering dataset loading, task definition, model training, evaluation, calibration, and clinical interpretation.

日本語の概要は準備中です。原文の説明を表示しています。

BioTender-max/awesome-bio-agent-skills2012026年7月2日 更新

Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1922026年8月21日 更新

Find and synthesize research papers, whitepapers, PDFs, technical reports, and academic sources with Firecrawl Research, using semantic paper search, related-paper expansion, and in-body verification over Firecrawl's paper index — largely biomedical and life-science literature from PubMed, bioRxiv, and medRxiv, plus arXiv preprints in CS, physics, and math. Use when the user wants a literature review, systematic review, survey of studies, paper summary, research landscape, or sourced synthesis from scholarly and industry publications, including clinical, drug, gene, disease, epidemiology, and public-health topics. Prefer this over a general web-research workflow whenever the evidence base is published papers rather than web pages.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/firecrawl-workflows1922026年8月21日 更新

Apply this skill whenever evaluating neurodegenerative disease research, protein misfolding, experimental rigor, or career longevity for women in STEM. Use this to channel the thinking of Virginia M.-Y. Lee, neuroscientist at the University of Pennsylvania known for her pioneering work on neurodegeneration. Trigger this skill when discussing Alzheimer's, Parkinson's, ALS, protein aggregation, cell-to-cell transmission of pathology, brain banking, or multidisciplinary scientific collaboration. It is highly relevant when users need critiques on biological models, advice on sustaining a long scientific career, or frameworks for translating clinical pathology into basic science.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/mimeographs1302026年8月19日 更新

Applies the epidemiological and aging research frameworks of Tamara B. Harris (epidemiologist, National Institutes of Health). Use this skill whenever analyzing health metrics in older populations, designing longitudinal studies, evaluating body composition (muscle quality vs. mass), assessing dementia risk factors, or interpreting paradoxical risk factors in geriatrics. Trigger this skill when the user asks about aging, longevity, functional decline, socioeconomic health disparities, or when evaluating clinical trial data where reverse causation or subgroup stratification might skew results.

日本語の概要は準備中です。原文の説明を表示しています。

K-Dense-AI/mimeographs1302026年8月19日 更新

Suede-affiliated ethical application of behavioral science to marketing decisions, including framing, anchoring, social proof, loss aversion, choice architecture, and friction. Use when the user needs a named psychological model, an evidence-aware application, and a testable hypothesis. NOT FOR: clinical or mental-health advice, deceptive dark patterns, page implementation (use suede-site-alchemy), or pricing design (use suede-pricing).

日本語の概要は準備中です。原文の説明を表示しています。

JasonColapietro/suede-creator-skills1272026年10月12日 更新

Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/skills1222026年10月9日 更新

Find and synthesize research papers, whitepapers, PDFs, technical reports, and academic sources with Firecrawl Research, using semantic paper search, related-paper expansion, and in-body verification over Firecrawl's paper index — largely biomedical and life-science literature from PubMed, bioRxiv, and medRxiv, plus arXiv preprints in CS, physics, and math. Use when the user wants a literature review, systematic review, survey of studies, paper summary, research landscape, or sourced synthesis from scholarly and industry publications, including clinical, drug, gene, disease, epidemiology, and public-health topics. Prefer this over a general web-research workflow whenever the evidence base is published papers rather than web pages.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/skills1222026年10月9日 更新

Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.

日本語の概要は準備中です。原文の説明を表示しています。

firecrawl/skills1222026年10月9日 更新