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cccskills

「research」の検索結果

4,953 件 ・ 関連度順

概要と使いどころ

Generates academic reviews for molecules in diseases using PubMed research. Invoke when user needs biomedical literature review with Vancouver citation format.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Use when converting medical text between academic and patient-friendly tones, translating medical jargon for patients, adapting research papers for public audiences, or rewriting clinical notes for patient handouts. Maintains medical accuracy while adjusting readability level.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Use when writing medical school personal statements, residency application essays, fellowship statements, or graduate school admissions essays. Crafts compelling narratives highlighting clinical experiences, research achievements, and career motivations for healthcare education 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Use when optimizing LinkedIn profiles for doctors, physicians, nurses, healthcare professionals, or medical researchers. Crafts compelling headlines, writes professional summaries, integrates healthcare keywords, and builds personal branding for medical careers.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Write comprehensive literature reviews for medical imaging AI research. Use when writing survey papers, systematic reviews, or literature analyses on topics like segmentation, detection, classification in CT, MRI, X-ray, ultrasound, or pathology imaging. Triggers on requests f...

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). ...

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates a first draft of a clinical meta-analysis paper. Input the research report (including Methods and Results sections), language, and title to automatically generate a complete paper draft including Abstract, Introduction, Discussion, and other sections, with automatic ...

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Automatically find references for academic paper Markdown files. Reads full paper text, identifies each knowledge point requiring citation (epidemiological data, mechanism descriptions, existing research conclusions, etc.), searches PubMed for 3-5 most relevant articles per kn...

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete two-sample Mendelian randomization research designs from a user-provided outcome, exposure or exposure family, and robustness direction. Use when a study centers on summary-statistics causal inference with instrument selection, harmonization, IVW-primary estimation, complementary estimators, sensitivity analyses, optional multivariable upgrades, and conservative evidence interpretation. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs complete research plans that integrate clinical variables with multi-omics data from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a study that combines clinical variables with transcriptomics, proteomics, metabolomics, epigenomics, or related omics layers for mechanism interpretation, biomarker development, risk stratification, treatment-response analysis, or translational use. It should define the clinical use case, alignment across data layers, feature-reduction and fusion logic, modeling route, mechanism-interpretation layer, validation ladder, and four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, accession numbers, sample counts, metadata completeness, platform coverage, literature references, PMIDs, DOIs, or validation status. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs discovery, modeling, and validation workflows for prognostic biomarkers in biomedical and clinical research. Always use this skill when the user needs a prognostic biomarker study blueprint rather than a diagnostic test protocol, predictive biomarker design, treatment recommendation, or a completed manuscript. Focus on endpoint family, follow-up horizon, time scale, candidate marker strategy, model-building logic, risk stratification framework, and internal/external validation requirements. Do not invent cohort size, event rate, assay readiness, literature support, or validation access.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs primary, secondary, and exploratory endpoints for biomedical and clinical research protocols. Always use this skill when a user needs to translate study aims into operational endpoint definitions with event rules, assessment timing, composite logic, interpretability, and protocol-stage auditability. Focus on endpoint precision, feasibility, clinical meaning, ambiguity reduction, and implementation readiness rather than generic study design advice.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete single-compound network-toxicology research designs from one exposure, one disease or toxic phenotype, and a validation direction. Use when a study centers on one compound–one disease link and needs target collection, overlap construction, enrichment, PPI hub prioritization, docking, optional transcriptomic cross-check, and conservative mechanistic synthesis. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete reference-grounded single-drug adverse-effect network-pharmacology research designs from a user-provided drug, adverse event, and desired evidence depth. Always use this skill when a user wants to design, plan, or upgrade a conventional network-pharmacology study centered on one fixed drug and one fixed adverse-effect endpoint, using drug-target prediction, adverse-event target collection, overlap analysis, PPI hub prioritization, enrichment interpretation, molecular docking, and optional orthogonal transcriptomic or literature validation. Covers five study patterns (canonical hub-first, cardiotoxicity or electrophysiology-oriented, immune-inflammatory adverse effect, organ-toxicity pathway context, translational validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, dependency/evidence map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, verified-reference pack, and self-critical risk 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete FAERS pharmacovigilance study designs for one-drug whole-profile safety mapping using signal detection, subgroup analysis, onset/seriousness characterization, and conservative label-gap 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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements. Always use this skill when a user has a general aim such as “explore a mechanism,” “study prognosis,” “investigate biomarkers,” or “look at treatment response,” but the objective is still too broad, non-operational, or too ambiguous to support protocol framing, design selection, analysis planning, or hypothesis design. Never assume that polished wording alone means the objective is actionable. Focus first on objective type, missing operational elements, scope discipline, and downstream-ready formulation.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs studies for predicting treatment response or resistance in biomedical and clinical research. Always use this skill when the user needs a treatment-response or resistance prediction study blueprint rather than a prognostic biomarker protocol, diagnostic test design, causal treatment-effect estimation, or a completed manuscript. Focus on responder definition, treatment context, baseline comparability, feature integration strategy, model development logic, validation architecture, and interpretation boundaries. Do not invent response rates, cohort size, assay readiness, regimen uniformity, literature support, or validation access.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs retrospective or prospective clinical cohort study protocols for biomedical and clinical research. Always use this skill when the user needs a cohort-based study plan rather than a general study idea, evidence summary, or mechanistic experiment design. Focus on cohort appropriateness, enrollment logic, baseline time-zero definition, follow-up structure, endpoint definition, variable collection, confounding control, and a coherent primary statistical analysis line. Do not invent data availability, follow-up completeness, outcome ascertainment quality, sample size adequacy, or causal interpretability.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Builds clear, executable, and auditable inclusion and exclusion criteria for biomedical and clinical research protocols. Always use this skill when a user needs to translate a target population into operational screening rules tied to chart fields, time windows, tests, procedures, prior therapies, exclusions, and reviewable edge cases. Focus on protocol-stage precision, ambiguity reduction, auditability, and screening reproducibility rather than generic study design advice.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Generates complete comparative network-toxicology research designs from a user-provided exposure pair, shared toxic phenotype, and validation direction. Use when a study centers on two related exposures under one outcome and needs target collection, shared-vs-specific target decomposition, enrichment, PPI hub prioritization, docking, optional transcriptomic cross-checks, and conservative mechanistic synthesis. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Compares multiple study-route options for the same biomedical research question and recommends one primary plan, while explicitly explaining why alternative routes are secondary, premature, weaker, or dependency-heavy. Always use this skill when the user already has a reasonably defined question but is unsure which main study route should anchor the project. Focus on plan comparison, route selection, dependency awareness, and primary-plan justification rather than full protocol drafting.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新

Designs internal, external, temporal, and functional validation strategies at the protocol stage for medical research studies.

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。

aipoch/medical-research-skills1,9552026年9月17日 更新