Evaluating the sampling effect of propensity score matching for reducing selection bias in medical data. [PDF]
Roh M, Yum S, Joo G, Jang JW, Im H.
europepmc +1 more source
ABSTRACT Machine learning (ML) is prevalent in land change modeling for automating transition rule specification. However, aspatial strategies are typically used to mitigate the imbalances characterizing multitemporal land cover (LC) datasets. While spatialized cost‐sensitive learning strategies including spatial sample weights (SSWs) have demonstrated
Alysha van Duynhoven +2 more
wiley +1 more source
Advanced Embryo Ploidy Classification Using Vision Transformers: Integration of Sequential Time-Lapse Imaging and Undersampling Techniques: A Retrospective Study. [PDF]
Avidiansyah MF +9 more
europepmc +1 more source
Evaluating machine learning approaches for multiple attack classification with improved computational efficiency in IoT networks. [PDF]
Alharby M.
europepmc +1 more source
Enhancing cardiotocography classification via ensemble learning and threshold optimization. [PDF]
Kong L +8 more
europepmc +1 more source
Feasibility Study for Dual Phase Free Breathing 3D bSSFP MRA With Preserved Eddy-Current Tolerance With Adaptive k-Space Lengths (PETAL) Acquisition. [PDF]
Ribeiro Salles Moura T +11 more
europepmc +1 more source
Extending real-time MRI of the oral cavity using simultaneous multislice and compressed sensing. [PDF]
Watson I +5 more
europepmc +1 more source
Physics-informed deep learning enables fast ultrahigh-resolution nuclear magnetic resonance spectroscopy. [PDF]
Bao J, Ni Y, Hu L, Zhan H.
europepmc +1 more source
Predicting the risk of asthma development in youth using machine learning models. [PDF]
Xie M, Xu C.
europepmc +1 more source

