“survival”的搜索结果

Analyze how long events take to occur, including records where observation ends before the event. Use Python to prepare data, fit and compare survival models, and evaluate predictions with measures suited to incomplete observations.

中文简介正在准备中。当前显示英语简介。

• Analyze time to events with incomplete observations
• Compare Cox models and Random Survival Forests
• Select features in datasets with many variables

Build and evaluate time-to-event models with scikit-survival, including records whose events remain unobserved when follow-up ends. Keep preprocessing separate from evaluation data, compare models, predict survival probabilities, and summarize censoring-aware metrics.

中文简介正在准备中。当前显示英语简介。

• Validate event indicators and follow-up times in local CSV data
• Train survival models without leaking evaluation data
• Evaluate survival probabilities with censoring-aware metrics

Builds and validates predictive time-to-event models on clinical and omics data with penalized Cox, random survival forests, gradient-boosted and deep survival models, and prediction-grade evaluation (Uno's C, time-dependent AUC, integrated Brier, calibration, competing risks). Use when building an individualized risk predictor or prognostic omics signature, choosing a survival model, or evaluating one beyond the C-index. For Kaplan-Meier, log-rank, and classical Cox hazard-ratio inference in a trial see clinical-biostatistics/survival-analysis.

中文简介正在准备中。当前显示原文说明。

Expert blueprint for survival games (Minecraft, Don't Starve, The Forest, Rust) covering needs systems, resource gathering, crafting recipes, base building, and progression balancing. Use when building open-world survival, crafting-focused, or resource management games. Keywords survival, needs system, crafting, inventory, hunger, resource gathering, base building.

中文简介正在准备中。当前显示原文说明。

Expert blueprint for survival games (Minecraft, Don't Starve, The Forest, Rust) covering needs systems, resource gathering, crafting recipes, base building, and progression balancing. Use when building open-world survival, crafting-focused, or resource management games. Keywords survival, needs system, crafting, inventory, hunger, resource gathering, base building.

中文简介正在准备中。当前显示原文说明。

Prepare and check research documents for clinical decision-support evaluation, including evidence profiles, cohort tables, survival plans, and model assessments. Work with aggregate or synthetic inputs, record sources and review status, and keep outputs outside patient care.

中文简介正在准备中。当前显示英语简介。

• Preparing research model evaluation documents
• Checking evidence profiles and source links
• Reviewing survival analysis plans

Analyze time until events such as recovery or relapse using Python. Account for censored observations, where the event has not been observed, create survival curves, compare groups, and estimate risk factors with Cox regression.

中文简介正在准备中。当前显示英语简介。

• Analyzing time to death or disease progression in clinical trials
• Comparing survival curves across treatment groups
• Estimating risk factors with Cox regression

Build reproducible empirical analyses in R, from data cleaning to statistical modeling and publication tables and figures. Covers economics, epidemiology, and machine learning approaches to causal inference, which estimates effects of interventions.

中文简介正在准备中。当前显示英语简介。

• Build a reproducible R or Quarto analysis workflow
• Compare regression models with progressively added controls
• Test robustness across samples and statistical methods

Build a survival-crafting game: resource gathering, inventory, crafting and a tech tree, needs (hunger/thirst/temperature), and base building. Use for a survival or crafting/base-building game.

中文简介正在准备中。当前显示原文说明。

Use when generating Kaplan-Meier survival curves from tabular survival data containing time, event status, and a precomputed risk group. Supports command-line parameter input, parameter validation, automatic time-unit handling, single-file PDF figure export, and session metadata capture.

中文简介正在准备中。当前显示原文说明。

Bevy ECS skill for survival loops. Keywords: Bevy, survival, hunger, warmth, day clock, crafting, ECS.

中文简介正在准备中。当前显示原文说明。

Thin Bevy genre router for Survival. Keywords: Bevy, Survival, genre, ECS, router.

中文简介正在准备中。当前显示原文说明。

Time-to-event modeling with scikit-survival: Cox PH (elastic net), Random Survival Forests, Boosting, SVMs for censored data. C-index, Brier, time-dependent AUC; Kaplan-Meier, Nelson-Aalen, competing risks. Pipeline/GridSearchCV compatible. Use statsmodels for frequentist, pymc for Bayesian, lifelines for parametric.

中文简介正在准备中。当前显示原文说明。

Art direction for survival and survival-horror gameplay spaces in Blender emphasizing resource props, crafting readability, and tension routes.

中文简介正在准备中。当前显示原文说明。

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.

中文简介正在准备中。当前显示原文说明。

Review spending and fundraising plans through six financial questions covering cash runway, customer economics, ownership dilution, alternatives, margins, and downside survival. Produce a verdict, conditions for funding, and three concrete next steps.

中文简介正在准备中。当前显示英语简介。

• Reviewing hiring plans against available cash
• Checking dilution before fundraising
• Assessing customer acquisition channel budgets

Guide an AI agent through ClawWork, an economic survival simulation where task rewards must cover API token costs. Defines a daily choice between work and learning, artifact submission, knowledge storage, and priorities based on the remaining balance.

中文简介正在准备中。当前显示英语简介。

• Choose work or learning based on the remaining balance
• Create and submit task artifacts for evaluation
• Save research findings to persistent memory

Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.

中文简介正在准备中。当前显示英语简介。

• Building a reproducible Stata analysis pipeline
• Comparing regression specifications in a paper table
• Checking causal estimates with robustness tests

Use when constructing a prognosis nomogram from survival-related clinical predictors, exporting the nomogram bundle and C-index table, and optionally rendering the final nomogram PDF. NOT for: univariate/multivariable Cox feature screening, calibration curves, ROC analysis, decision-curve analysis, or non-survival outcomes.

中文简介正在准备中。当前显示原文说明。

Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.

中文简介正在准备中。当前显示原文说明。

Cancer genomics (TCGA et al.) via cBioPortal REST API. Retrieve somatic mutations, CNAs, expression, clinical data (survival/stage/treatment) across thousands of studies. Use for TMB, oncoprints, survival analysis. For population frequencies use gnomad-database; for drug-gene interactions use opentargets-database.

中文简介正在准备中。当前显示原文说明。

Performs time-to-event analysis for clinical trials including Cox proportional hazards regression with PH diagnostics, restricted mean survival time (RMST) under non-PH, competing risks via Fine-Gray vs cause-specific Cox, weighted log-rank and MaxCombo for non-proportional hazards, recurrent events (Andersen-Gill, PWP, WLW), and interval-censored data. Use when analyzing time-to-event endpoints (OS, PFS, DOR, TTR, TTNT) in oncology or other clinical trials.

中文简介正在准备中。当前显示原文说明。

Purify water from wild sources using boiling, filtration, and chemical methods. Covers source assessment and priority ranking, sediment pre-filtering, method selection (boiling, chemical, UV, filter), altitude-adjusted boiling procedure, chemical treatment dosages, and safe storage practices. Use when needing drinking water in a wilderness setting, when available water sources are of unknown quality, in an emergency survival situation where dehydration is a risk, or when making water safe for cooking or wound cleaning.

中文简介正在准备中。当前显示原文说明。

Start and maintain a fire using friction, spark, and solar methods. Covers site selection, material grading (tinder/kindling/fuel), fire lay construction (teepee, log cabin, platform), ignition techniques (ferro rod, flint & steel, bow drill), flame nurturing, and Leave No Trace extinguishing. Use when needing warmth, light, or a signal in a wilderness setting, when boiling water for purification, when cooking foraged food, or in an emergency survival situation requiring heat or morale support.

中文简介正在准备中。当前显示原文说明。