MEMS motion tracking system for surgical robot ROCH-1. - Ryszard Leniowski; Lucyna Leniowska (MMAR, 2013)

Application of Artificial Neural Networks for the Diagnosis of the Condition of the Arterio-venous Fistula on the Basis of Acoustic Signals. - Marcin Grochowina; Lucyna Leniowska; Piotr Dulkiewicz (Brain Informatics and Health, 2014)

Comparison of SVM and k-NN classifiers in the estimation of the state of the arteriovenous fistula problem. - Marcin Grochowina; Lucyna Leniowska (FedCSIS, 2015)

The new method of the selection of features for the k-NN classifier in the arteriovenous fistula state estimation. - Marcin Grochowina; Lucyna Leniowska (FedCSIS, 2016)

Analysys of the impact of disturbance on the arteriovenous fistula state classification. - Marcin Grochowina; Lucyna Leniowska (FedCSIS (Communication Papers), 2017)

Design and implementation of a device supporting automatic diagnosis of arteriovenous fistula. - Marcin Grochowina; Lucyna Leniowska (SPA, 2018)

Detecting of the rolling bearing state based on acoustic signal and the k-NN classifier. - Dorota Gil; Marcin Grochowina; Lucyna Leniowska (SPA, 2019)

An application of wavelet transform for non-invasive evaluation of arteriovenous fistula state. - Marcin Grochowina; Kamil Wojnar; Lucyna Leniowska (SPA, 2019)

Applying DCT Combined Cepstrum for the Assessment of the Arteriovenous Fistula Condition. - Marcin Grochowina; Lucyna Leniowska (ICCS (3), 2021)

Intelligent candidate recommendation system based on experimental calculation of the similarity model. - Ryszard Leniowski; Lucyna Leniowska; Michal Wronski; Krzysztof Tomecki; Marcin Grochowina; Lukasz Ryk (FUZZ-IEEE, 2022)