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towardsdatascience.com /1 week ago

Survival Analysis for Data Drift and ML Reliability

Treating model degradation as a time-to-failure problem The post Survival Analysis for Data Drift and ML Reliability appeared first on Towards Data Science.

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insurancebusinessmag.com /1 day ago

WTW extends mortality model to PRT market as insurer competition grows

The geospatial model, trained on nearly four million life-years of data, is now available to carriers pricing longevity risk

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theheartysoul.com /1 week ago

The Simple Functional Test Doctors Use to Help Predict Longevity After 75

Discover the longevity functional tests doctors use to predict survival after 75, including the sitting-rising test, gait speed The post The Simple Functional Test Doctors Use to H...

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medinform.jmir.org /1 month ago

Predicting 5-Year Mortality in Non–Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development an...

Background: Non–small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic prediction clinically essential....

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k-d-w.org /1 week ago

Sebastian Pölsterl: scikit-survival 0.28.0 released

I am pleased to announce the release of scikit-survival 0.28.0. A highlight of this release is the support for Polars DataFrames alongside pandas DataFrames via the Narwhals datafr...

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medinform.jmir.org /1 month ago

Predicting End-Stage Renal Disease and Mortality in Chronic Kidney Disease Using Machine Learning: Retrospective Cohort...

Background: Chronic kidney disease (CKD) is a global health burden characterized by heterogeneous progression trajectories. Without timely and appropriate management, CKD can lead...

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habr.com /1 month ago

Критерии выживания и случайность — 5

Продолжаем data mining путешествие в погоне за удачей. Адаптивность — последний фактор в нашем разборе, хотя и не последняя статья серии. Если интеллект отвечает на вопрос «насколь...

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journals.plos.org /1 month ago

Incorporating variation in death times improves predictions of ectotherm responses to stressful temperatures

by Garrison W. Bullard, Lauren B. Buckley, Joel G. Kingsolver Predicting survival of ectotherms in stressful and variable thermal environments is an essential challenge in this er...

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informatics.bmj.com /1 month ago

Machine learning-based prediction of a high-risk kidney function trajectory class after acute kidney injury

Objectives Monitoring kidney function after acute kidney injury (AKI) hospitalisation is essential for identifying patients at risk of rapid progression. This study developed a mac...

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fightaging.org /2 weeks ago

An Insurance Industry Viewpoint on the Utility of Aging Clocks

Members of the life insurance industry have typically been far ahead of the rest of the general public outside the life sciences when it comes to an appreciation of progress toward...

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