「ml」の検索結果

Reads, validates, and prepares CDISC SDTM and ADaM clinical trial data for analysis. Covers SDTM domain joins (DM, AE, EX, VS, LB, DS), ADaM architecture (ADSL, BDS, OCCDS, ADTTE) with traceability, treatment-emergent AE conventions, baseline derivation, SUPPQUAL/NSV handling, Define-XML 2.1, and Pinnacle 21 / CORE validation. Use when working with clinical trial datasets in CDISC SDTM/ADaM format, preparing analysis-ready data, or validating for regulatory submission.

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Build a differential-ready consensus peakset from per-replicate ATAC-seq peaks using iterative overlap removal, fixed-width re-centering, and majority-rule overlap. Use when generating a stable peak coordinate system for downstream differential accessibility, ML feature engineering, cross-sample comparison, or fixed-width peak counts; covers Corces 2018 iterative overlap (501 bp), DiffBind summit re-centering, and ENCODE consistency rules.

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Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

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。

Determines if patient meets ICD-10 criteria for transsexualism. Triggered when a clinician uses ICD-10 for diagnostic purposes in gender identity assessment.

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Recommends RT-CGM devices for adult patients with well-controlled type 1 diabetes who are willing and able to use the devices on a nearly daily basis. Trigger phrases include 'Controlled T1DM patient interested in CGM' and 'Consider RT-CGM for glycemic stability in well-controlled T1DM'.

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Suggests short-term, intermittent real-time CGM use in adult patients with type 2 diabetes not on prandial insulin who have A1C ≥7% and are willing and able to use the device. Triggered by phrases such as “T2DM basal-only, A1C ≥7%, consider intermittent CGM” or “Short-term CGM for non-prandial T2DM with elevated A1C”.

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Suggests real-time CGM over no CGM for outpatients with type 2 diabetes who use insulin and/or sulfonylureas and are at high risk for hypoglycemia to detect and prevent low glucose events. Consider when initiating CGM in T2D patients on insulin/SU with a history of severe hypoglycemia or impaired awareness of hypoglycemia (IAH).

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This skill checks for contraindications or sources of inaccuracy that may affect continuous glucose monitoring (CGM) reliability in hospitalized adults. It is triggered when clinicians ask, “Are there factors that could make CGM unreliable?” or when assessing for skin infection, hypoperfusion, hypovolemia, vasoactive/pressor therapy, or medications such as acetaminophen >4 g/day, dopamine, vitamin C, or hydroxyurea.

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Recommends real-time CGM with confirmatory POC-BG for insulin dosing adjustments in insulin-treated hospitalized adults at high risk of hypoglycemia when resources and training are available. Triggers include: "Should we use CGM for insulin adjustments?" or "Is CGM appropriate for this patient?

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。

This skill suggests using real-time continuous glucose monitoring (CGM) rather than no CGM for outpatients with type 2 diabetes (T2D) who take insulin and/or sulfonylureas and are at high risk for hypoglycemia. It is triggered by clinician questions such as "Should I use CGM for this T2D patient on insulin or sulfonylureas with high hypoglycemia risk?" or "Is CGM indicated for this patient?"

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。

Recommends CGM over SMBG for type 1 diabetes patients on multiple daily injections to reduce hypoglycemia risk. Triggered by clinician questions such as "Should I use CGM or SMBG for this T1D patient on MDI?" or "Is CGM preferred for glucose monitoring in this patient?"

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This skill suggests continuing personal CGM with or without ADIP rather than discontinuation for inpatients already using it who are at high risk for hypoglycemia. Trigger phrases include "Should I continue or discontinue personal CGM for this inpatient who is already using it?" and "Is it appropriate to maintain personal CGM during hospitalization?"

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This skill confirms whether a hospital has the necessary policies and expertise to support inpatient insulin pump therapy, including informed consent, standardized order sets, and device management guidance for imaging and surgical procedures. Triggered by questions such as "Are hospital policies and expertise in place for insulin pump use?" to ensure safe continuation of pump therapy in noncritical illness.

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If CGM fails or is removed, revert the insulin pump to manual mode provided basic criteria for pump use in hospital are still met. Trigger phrase: "CGM failed, should we switch pump to manual mode?

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。

Verify that insulin pump supplies (provided by patient or family) will be available throughout the hospitalization to support continued pump use. Triggered by questions such as "Do we have sufficient pump supplies for the hospital stay?"

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Transition insulin pump to scheduled subcutaneous basal bolus insulin when anticipated hospital length of stay exceeds 1 to 2 days and pump expertise is unavailable. Triggers include: "Patient expected to stay >2 days, should we switch pump to scheduled insulin?

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Calculates initial and escalating dose for pubertal induction hormone therapy based on patient weight or body surface area. Triggers include patient eligible for sex hormone treatment, ready to start hormones.

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If CGM is not available, continue monitoring blood glucose with point-of-care testing as an alternative option. Trigger phrases include: "CGM is not available, what should we use for glucose monitoring?

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Suggests initiating inpatient CGM for select diabetic patients at high risk for hypoglycemia based on Table 3 criteria. Triggers include "Should I initiate CGM for this hospitalized diabetic patient at high risk for hypoglycemia?" or "Is inpatient CGM warranted for this patient?"

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。

Determines if adolescent meets criteria for GnRH agonist treatment to suppress pubertal development. Triggers include adolescent requesting to suppress puberty, adolescent with gender dysphoria seeking pubertal blockade, or clinician noting Tanner G2/B2 with request for hormone suppression.

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。

This skill determines whether inpatient diabetic patients meet high-risk criteria for CGM initiation using Table 3 factors such as age ≥65 years, BMI ≤27 kg/m², type 1 diabetes, insulin regimen, and specific clinical conditions. It is triggered by clinician questions like "Should I assess this inpatient for CGM initiation based on hypoglycemia risk?" or "Is this patient a candidate for inpatient CGM?"

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Considers adapting the basal insulin rate at hospital admission for patients using insulin pump therapy. Triggered by clinician questions such as "Should we adjust the basal rate upon admission for pump therapy?" or when evaluating pump continuation versus transition to scheduled subcutaneous insulin.

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。

Assess whether a hospitalized adult with diabetes on insulin pump therapy remains a candidate for continued inpatient pump use. Consider triggers such as the clinician asking "Is this patient appropriate to continue insulin pump in hospital?" and evaluate for impaired consciousness, inability to adjust pump settings, critical illness, DKA, or hyperosmolar hyperglycemic state.

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。