Cox proportional hazards model
PulseAugur coverage of Cox proportional hazards model — every cluster mentioning Cox proportional hazards model across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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New foundation model SurvICL outperforms Cox model in survival analysis
Researchers have introduced SurvICL, a new foundation model designed for in-context survival analysis. This model aims to outperform traditional methods like the Cox proportional hazards model, particularly on smaller c…
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New research explores advanced survival analysis techniques using deep learning and optimization
Two new research papers explore advanced techniques for survival analysis, a method used to predict the time until an event occurs. The first paper, focusing on outcome-dependent truncation and censoring, demonstrates t…
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New method improves scalability for Cox regression analysis
Researchers have developed a new method for scalable Cox regression, addressing computational challenges in large-scale datasets. The approach utilizes grouped risk sets and a sharper LogSumExp rate analysis, improving …
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New MultiSigBERT model enhances oncology survival prediction with multimodal data
Researchers have developed MultiSigBERT, a novel framework for multimodal sequential survival modeling in oncology. This approach integrates heterogeneous data sources, including narrative clinical reports and structure…
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AI models outperform FRAX in predicting fracture risk using EHR and DXA data
Researchers have developed and validated new models for predicting fracture risk in adults over 50, utilizing data from dual-energy X-ray absorptiometry (DXA) and electronic health records (EHR). These models, including…
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New AI bias-correction framework for Cox regression in clinical studies
Researchers have developed a new bias-correction framework for the Cox proportional hazards model, specifically designed for situations where covariates are extracted using AI from unstructured clinical records. This fr…
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New latent ODE model enhances heart failure prediction from cardiac MRI
Researchers have developed a novel latent dynamical model using neural ordinary differential equations (ODEs) to analyze cardiac magnetic resonance imaging (CMR) data. This model encodes bi-ventricular anatomy and full-…
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Federated learning shows promise for healthcare survival analysis · 2 sources tracked
A new paper evaluates federated learning for survival analysis in healthcare, specifically on breast cancer data across multiple institutions. The study compared three survival models (Cox Proportional Hazards, DeepSurv…
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New R package aids personalized medicine by estimating treatment effects in complex risk scenarios
Researchers have developed a new R package called `crsurvlearners` to help estimate conditional average treatment effects (CATEs) in competing risks settings. This is particularly useful in personalized medicine where u…
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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…
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KANs advance survival analysis with new deep learning model
Researchers have developed KAPLAN-HR, a new deep learning model based on Kolmogorov-Arnold Networks (KANs) for survival analysis. This model can estimate conditional hazard rates as a joint function of covariates and ti…
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AI Recommender Improves Predictive Study Design with Explainable Insights
Researchers have developed an Exploratory AI Recommender to aid in the design of high-dimensional predictive studies, particularly in healthcare. This framework uses flexible AI to identify complex data patterns and exp…