「ml」の検索結果

Classify constitutional (germline) copy number variants for clinical reporting using the 2019 ACMG/ClinGen technical standards points-based framework, with ClassifyCNV and AnnotSV for semi-automated scoring. Covers the separate copy-number-loss and copy-number-gain rubrics, the five-tier classification, ClinGen haploinsufficiency/triplosensitivity and dosage-sensitive regions, de novo and segregation evidence, and population-frequency benign evidence. Use when assigning pathogenic/likely-pathogenic/VUS/likely-benign/benign to a constitutional CNV, scoring a CNV against ACMG/ClinGen criteria, or distinguishing the automatable evidence from the case-specific evidence requiring manual input.

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Analyzes CRISPR drug-modifier (chemogenomic) screens with drugZ (Colic et al. 2019 Genome Med), a bidirectional Z-score method that identifies synthetic-lethal sensitizing genes and resistance-conferring suppressor genes from vehicle vs drug comparisons. Covers vehicle-anchored design (not Day-0), the bidirectional Z math giving greater sensitivity to small-effect hits than MAGeCK / STARS / edgeR / RIGER on drug screens, per-gene sumZ and normZ, synth (sensitizer) vs supp (suppressor) FDR, multi-dose handling, integration with control sgRNAs, and comparison with MAGeCK MLE with dose covariate. Use when running a drug-modifier CRISPR screen, identifying sensitizing or resistance genes for a drug candidate, choosing drugZ vs MAGeCK MLE for chemogenomic analysis, troubleshooting low-effect drug screens where MAGeCK lacks sensitivity, or designing a drug-screen layout (vehicle vs drug arms).

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Queries ClinVar for variant pathogenicity classifications, ClinGen VCEP curations, and somatic-vs-germline interpretations via REST API, weekly VCF, or bulk XML. Use when determining clinical significance, triangulating conflicting interpretations, or aggregating evidence against the ACMG/AMP framework with ClinGen SVI specifications.

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Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML. Use when testing whether a molecular phenotype (expression, methylation, protein) mediates a treatment-outcome relationship, decomposing exposure-mediator interaction via VanderWeele 4-way, screening high-dimensional EWAS mediators, or running MR-based mediation when sequential ignorability is implausible.

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Calculates tumor mutational burden from WES/WGS/panel data with Friends of Cancer Research harmonization equations, per-assay calibration (FDA 10/Mb = 7.8 TSO500 = 8.4 OncomineTML), synonymous/indel/germline filtering, hypermutator tiering, blood TMB, and integration with HLA-LOH and neoantigen quality (Luksza 2017 fitness). Use when assessing ICI eligibility under tumor-specific cutoffs (McGrail 2021), comparing tissue vs bTMB, or auditing TMB-H reporting against ESMO 2024 and FDA pembrolizumab pan-tumor 2020.

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Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

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Determines if current hormone levels are within target range for affirmed gender (e.g., testosterone 400-700 ng/dL for transgender males, estradiol 100-200 pg/mL for transgender females). Triggers include patient on hormone therapy and time for level check.

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Adjusts intravenous bisphosphonate dosing and infusion duration for patients with hypercalcemia of malignancy and renal insufficiency (creatinine clearance <60 mL/min). Triggered when a clinician encounters renal impairment and asks how to modify zoledronic acid or pamidronate infusion rates.

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Determines when to test for germline KCNJ5 mutations indicating familial hyperaldosteronism type III in very young patients with primary aldosteronism. Triggered by severe early-onset hypertension with hypokalemia in infants or young children (<20 years) with confirmed PA.

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Identifies patients with a positive aldosterone-to-renin ratio screening who may proceed directly to subtype testing without confirmatory testing based on specific clinical criteria. Triggers include spontaneous hypokalemia, baseline plasma aldosterone concentration >100 pg/mL (CLEIA), renin suppression, or a clinician questioning the need for a confirmatory test after a positive screen.

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Determines the appropriate IV pamidronate dose (60‑90 mg) and infusion duration (2‑24 h) for adults with hypercalcemia of malignancy based on renal function. Triggered when a clinician orders pamidronate and asks how to adjust for kidney dysfunction (eGFR < 60 mL/min/1.73 m²).

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Draft a Workflow Phase 4 technical spec from an intake (and optionally a BRD + scout + research memo). The spec defines how the system will change: design (C4 + UML + dependency graph in PlantUML), data, APIs, tests, rollout, rollback. Output lives at `docs/specs/<slug>.md`. Never self-approves — approval happens via `/approve-direction`.

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Extract every PlantUML block from docs/specs/<slug>.md and render each to SVG under docs/specs/_rendered/<slug>/, with an index.md listing them in order. Run this before /approve-direction so the reviewer sees pictures instead of raw PlantUML.

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Write ML papers for NeurIPS/ICML/ICLR: design→submit.

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54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.

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Azure Machine Learning SDK v2 for Python. Use for ML workspaces, jobs, models, datasets, compute, and pipelines.

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Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

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Search 8,400+ AI and ML jobs across 489 companies, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP

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Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.

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AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

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長大な設計文書・Pull Request・Issueを読み解き、図と短い文を組み合わせた解説HTMLを生成してブラウザで開く。生成したページ内の識別子を指定すると、その項目だけを掘り下げたページも作る。

WAV/動画音声を単一パスGPU転写（mlx-whisper）した後、fulltextを意味区切りでN分割しLLM改行だけを並列化してSRT字幕を高速生成する /srt の高速版。日本語トーク動画用。「/srt-fast」で実行。

Use when writing C# / VB.NET / F# code that reads, writes, manipulates, or exports Excel (.xlsx / .xls) files, generates PDF or HTML from Excel, or produces data-driven reports with FlexCel Studio for .NET (TMS Software). Triggers include Excel/xlsx from C#, XlsFile, FlexCelReport, FlexCelPdfExport, FlexCelHtmlExport, FlexCelImgExport, ExcelFile, PdfWriter, .NET Excel export, ASP.NET Excel generation, .NET MAUI Excel, Native AOT + Excel, and Excel reporting from .NET.

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Use when writing Delphi / FreePascal / C++Builder code that reads, writes, manipulates, or exports Excel (.xlsx / .xls) files, generates PDF or HTML from Excel, or produces data-driven reports with FlexCel Studio for VCL and FireMonkey (TMS FlexCel). Triggers include Excel/xlsx from Delphi, TXlsFile, TFlexCelReport, TFlexCelPdfExport, TFlexCelHtmlExport, FireMonkey Excel export, Lazarus Excel, and Excel reporting from Pascal.

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。