The Lancet

Development and validation of a machine-learning model to reduce futile procurements in donations after circulatory death in liver transplantation in the USA…

We show that, compared with surgeon predictions and existing risk-prediction tools, our machine-learning model can enhance ...
The Lancet

Reducing futile donation after circulatory death procurement with machine learning

Donation after circulatory death (DCD) procurements provide an opportunity to alleviate the limited organ supply for solid ...
IEEE

Discretized Urban Path Loss Modeling at 3.5 GHz Using Geospatial Features and Machine Learning Techniques: From Regression to Classification

Abstract: Accurately modeling and predicting urban path loss is a challenging task due to the fact that conventional regression models yield continuous estimates that can hide important performance ...
IEEE

Machine Learning-Based Logistic Regression with Hybrid Loss Function for Enhanced Spectrum Sensing

Abstract: In the field of radio technology, the scarcity of spectrum resources has become increasingly severe, while demands for higher accuracy and speed in spectrum sensing technologies continue to ...