Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), 37-41, 2023. [PUMA: Complexity Computational Consciousness Information Locked-In Measures Modeling Neuroscience Prediction Predictive Processing Signal Syndrome Theory Training algorithms and data learning modeling models processing zno machine]
Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, (35):93–101, IEEE, September 2023. [PUMA: Comparative Computer Self-Supervised Study Unlabelled Vision yaff data learning] URL
Stability selection enables robust learning of partial differential equations from limited noisy data. arXiv, 2019. [PUMA: (cs.LG) (math.NA) (physics.data-an) Analysis Computer FOS Mathematics Numerical Physical Probability Statistics data information learning machine sciences xack] URL
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: AI CNN Communications DICOM Diagnosis Digital HCC Imaging Individual ML MVI Medicine NAFLD NASH Prognosis Reporting TACE TRIPOD Transparent WSIs a and artificial carcinoma chemoembolisation convolutional data deep diagnostic disease fatty for hepatocellular images imaging in integration intelligence invasion learning liver machine microvascular model multimodal multivariable network neural non-alcoholic of or prediction slide steatohepatitis support system topic_lifescience transarterial whole zno]
Automated algorithm selection: Survey and perspectives. Evol. Comput., (27)1:3--45, MIT Press, 2019. [PUMA: algorithm analysis approaches automated combinatorial configuration continuous data exploratory feature-based landscape learning machine metalearning optimisation selection streams zno]
Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)January 2024. [PUMA: AutoML analysis classification data learning machine problems topic_federatedlearn visualization xack yaff]