452 件 ・ 関連度順
概要と使いどころ
Use when drafting a grant or challenge proposal for a radiology or medical AI project, including a Korean government industry-academia plan. Structures significance, innovation, approach, aims, milestones and consortium roles, keeping claims evidence-based and executable.
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。
Use when a tabular dataset (CSV, Excel, Parquet, Stata, SAS) needs a data dictionary. Profiles every variable (type, levels, range, missingness) into codebook.md and codebook.json and flags coded values of unknown meaning as [NEEDS DICTIONARY] instead of guessing.
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。
Use when you need full-text PDFs for a list of DOIs, such as a meta-analysis screening set. Batch-downloads open-access copies via Unpaywall, PMC, OpenAlex and Crossref, lists paywalled papers for manual access, and can convert PDFs to Markdown.
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。
Use when choosing where to submit a manuscript. Matches the abstract against curated journal profiles and returns ranked picks with scope fit, AI-disclosure policy, an acceptance-readiness pre-flight and a reject-fallback cascade. Impact and APC figures may be stale.
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。
Use when looking for research topics a longitudinal cohort database can answer (NHIS, UK Biobank, an institutional EMR or registry). Profiles the cohort, matches PI expertise, scans literature saturation and returns ranked topic proposals with gap evidence.
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。
Use when preparing an academic talk such as a journal club, grand rounds, seminar, conference presentation, or lecture/teaching deck. Analyzes the source, drafts audience-adapted speaker scripts, builds or augments the PPTX with speaker notes and prepares Q&A.
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。
Renamed to /imaging-data in v6 (removed in v7).
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。
Use when a manuscript needs a copy-edit for consistency and non-native English clarity. Flags abbreviation, US/UK spelling, en-dash range, P/p, hyphenation, number-style and unit-spacing issues, then polishes style only. AI-tell removal is /humanize.
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。
Use when references in a .bib file (often from /search-lit) should land in Zotero and Obsidian. Syncs them to the Zotero library, writes Obsidian literature notes and extracts cross-cutting concept notes once enough accumulate. A folder of PDFs is /obsidian-paper-vault.
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。
Use when an institutional Word form (.doc/.docx IRB protocol, ethics application, grant template) must be filled without breaking its styles, tables, fonts or page layout. Renders content drafted by /write-protocol into the template; CJK-aware.
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。
Use when reviewing someone else's manuscript for a journal, such as after a review invitation or for a revised R1/R2 version. Drafts a structured, constructive review in the journal's format. Never for your own manuscript; that is /self-review.
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。
Use when each author needs an ICMJE Conflict of Interest disclosure form (coi_disclosure.docx) for submission. Clones a pre-filled synthetic seed with every item marked None and replaces only date, name and manuscript title, so most authors just confirm or amend.
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Use when turning a folder of research PDFs into Obsidian notes, even if Obsidian is not named. Writes one templated literature note per paper and extracts cross-linked atomic concept notes, never overwriting existing ones. A .bib or Zotero library is /lit-sync.
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。
Use when data needs statistical analysis. Runs reproducible Python/R code for Table 1, diagnostic accuracy, agreement, regression, survival, propensity score, survey-weighted and repeated-measures models, with publication tables. Sample size is /calc-sample-size; pooling studies is /meta-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。
Use when checking a radiology or medical AI study design before drafting or submission. Reviews the analysis unit, cohort logic, leakage risks, comparator, validation strategy and reporting-guideline fit. AI-vs-expert benchmarks are /design-ai-benchmarking.
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。
Use when designing a study that benchmarks AI systems against a human-expert panel, before data collection. Plans the arms, decoupled rubrics with anchors, planted calibration probes, reviewer panel, inter-rater reliability targets and LLM-as-judge versus human adjudication.
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。
Renamed to /model-assessment in v6 (removed in v7).
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。
Use when clinical data may contain PHI and must be de-identified before any LLM-assisted analysis. A local Python script (no network or AI calls) detects identifiers with regex and heuristics in 11 country locale packs, with interactive terminal review.
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。
Use when exposure, outcome, covariate or eligibility definitions and cutoffs need a citable basis before the protocol. Reads the data dictionary first, then maps each variable to a guideline or published definition and the database columns in a citation-backed table.
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。
Renamed to /model-selection in v6 (removed in v7).
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。
Use when a medical AI paper should be found and cited by AI search engines and RAG tools. Optimizes the title, abstract, summary box (Key Points, Research in Context), keywords, preprint, GitHub README/CITATION.cff and Hugging Face card, returning a visible pass/fail checklist.
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。
Use when comparing an exposure-outcome association across countries with parallel national surveys (KNHANES, NHANES, CHNS). Harmonizes variables, runs parallel weighted analyses and builds comparison tables for 2-country (KR+US) or 3-country (KR+US+CN) designs.
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。
Use when choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.
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。