medical-6

Kidney Function

3260 papers • 126 benchmarks • 313 datasets

Continuous prediction of urine production in the next 2h as an average rate in ml/kg/h. The task is predicted at irregular intervals.

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These leaderboards are used to track progress in kidney-function-6

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Most implemented papers

Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML

P. Thoral, R. V. D. Water, Hendrik Schmidt, Paul Elbers, Bert Arnrich, P. Rockenschaub•Wed Jun 07 2023

This work introduces Yet Another ICU Benchmark (YAIB), a modular framework that allows researchers to define reproducible and comparable clinical ML experiments and offers an end-to-end solution from cohort definition to model evaluation, and provides work to the clinical ML community to accelerate method development and enable real-world clinical implementations.

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Kidney segmentation in neck-to-knee body MRI of 40,000 UK Biobank participants

R. Strand, Taro Langner, Andreas Östling, Lukas Maldonis, Albin Karlsson, Daniel Olmo, Dag Lindgren, Andreas Wallin, Lowe Lundin, H. Ahlström, J. Kullberg•Thu Jun 11 2020

A pipeline for automated segmentation of parenchymal kidney volume in UK Biobank neck-to-knee body MRI is proposed, and algorithmic quality ratings enabled the exclusion of outliers and potential failure cases.

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Performance Analysis of Machine Learning Algorithms in Chronic Kidney Disease Prediction

S. Sakib, Iftekhar Ahmed, Tanzil Ebad Chowdhury, Biggo Bushon Routh, Nafisa Tasmiya, Adil Ahmed Chowdhury•Tue Oct 11 2022

This study designed and suggested disease predictive computer-aided designs for the diagnosis of CKD and found that Random Forest as well as Logistic Regression showed an outstanding 99% accuracy.

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MLC at HECKTOR 2022: The Effect and Importance of Training Data when Analyzing Cases of Head and Neck Tumors using Machine Learning

M. Riegler, P. Halvorsen, Steven Hicks, Vajira Lasantha Thambawita, Andrea M. Storaas•Tue Nov 29 2022

The work done by team MLC for the 2022 version of the HECKTOR grand challenge held at MICCAI 2022 is presented, concluding that the simple methods were not able to compete with the highest-ranking submissions, but they still obtained reasonably good scores.

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