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ENTITY survival analysis

survival analysis

PulseAugur coverage of survival analysis — every cluster mentioning survival analysis across labs, papers, and developer communities, ranked by signal.

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  1. 2026-06-03 research_milestone A new decision-focused approach for survival analysis was introduced, optimizing for NDCG to improve outcomes in allocation tasks. source
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  1. TOOL · CL_154541 ·

    Tabular foundation models adapted for survival analysis via classification

    Researchers have developed a novel classification-based framework that enables tabular foundation models (TFMs) to perform survival analysis. This method reformulates time-to-event outcomes as a series of binary classif…

  2. TOOL · CL_95793 ·

    New framework models metro usage lifecycle with HSMM and survival analysis

    Researchers have developed a new framework integrating Hidden Semi-Markov Models (HSMM) with survival analysis to study long-term metro usage patterns. This method, applied to Shanghai metro data from 2021-2024, identif…

  3. TOOL · CL_68307 ·

    New survival analysis method boosts organ allocation efficiency

    Researchers have developed a new decision-focused learning approach for survival analysis, aiming to better align predictive models with their downstream allocation tasks. This method optimizes for Normalized Discounted…

  4. RESEARCH · CL_68160 ·

    Tabular foundation models show promise for time-series prediction

    Researchers are exploring the application of tabular foundation models (TFMs) to complex time-series prediction tasks, particularly in prognostics and health management (PHM) and survival analysis. These models, adapted…

  5. TOOL · CL_59018 ·

    Survival analysis evaluation metrics criticized in new position paper

    A new position paper published on arXiv critiques the prevalent use of the C-index metric in survival analysis, arguing that it often misaligns with the actual modeling objectives and can be misleading due to implicit c…

  6. TOOL · CL_39983 ·

    New estimators improve changepoint detection evaluation

    Researchers have developed new non-parametric estimators, KM-ARL and KM-ADD, for evaluating quickest changepoint detection (QCD) methods. These estimators address the limitations of traditional ARL and ADD metrics when …