| PCG classification using a neural network approach I Grzegorczyk, M Soliński, M Łepek, A Perka, J Rosiński, J Rymko, ... 2016 computing in cardiology conference (CinC), 1129-1132, 2016 | 61 | 2016 |
| Automatic cough detection based on airflow signals for portable spirometry system M Soliński, M Łepek, Ł Kołtowski Informatics in medicine unlocked 18, 100313, 2020 | 38 | 2020 |
| Double pulse Laser Induced Breakdown Spectroscopy measurements on ITER-like samples S Almaviva, L Caneve, F Colao, P Gasior, M Kubkowska, M Łepek, ... Fusion Engineering and Design 96, 848-851, 2015 | 31 | 2015 |
| Measurements of deuterium retention and surface elemental composition with double pulse laser induced breakdown spectroscopy S Almaviva, L Caneve, F Colao, G Maddaluno, N Krawczyk, A Czarnecka, ... Physica Scripta 2016 (T167), 014043, 2016 | 19 | 2016 |
| Classification of atrial fibrillation in short-term ECG recordings using a machine learning approach and hybrid QRS detection M Soliński, A Perka, J Rosiński, M Łepek, J Rymko 2017 Computing in Cardiology (CinC), 1-4, 2017 | 10 | 2017 |
| Spatial evolution of Hindmarsh–Rose neural network with time delays M Łepek, P Fronczak Nonlinear Dynamics 92, 751-761, 2018 | 9 | 2018 |
| Exact combinatorial approach to finite coagulating systems through recursive equations M Łepek, P Kukliński, A Fronczak, P Fronczak Reports on Mathematical Physics 84 (1), 117-130, 2019 | 5 | 2019 |
| Combinatorial solutions to coagulation kernel for linear chains M Łepek, A Fronczak, P Fronczak Physica D: Nonlinear Phenomena 415, 132756, 2021 | 4 | 2021 |
| Coagulation with product kernel and arbitrary initial conditions: Exact kinetics within the Marcus-Lushnikov framework A Fronczak, M Łepek, P Kukliński, P Fronczak Physical Review E 99 (1), 012104, 2019 | 4 | 2019 |
| Scaling theory of fractal complex networks: Bridging local self-similarity and global scale-invariance A Fronczak, P Fronczak, M Samsel, K Makulski, M Łepek, MJ Mrowinski arXiv preprint arXiv:2306.13751, 2023 | 3 | 2023 |
| Coalescense with arbitrary-parameter kernels and monodisperse initial conditions: A study within combinatorial framework M Łepek, A Fronczak, P Fronczak Reports on Mathematical Physics 88 (1), 89-113, 2021 | 3 | 2021 |
| 12-lead ECG Arrhythmia Classification Using Convolutional Neural Network for Mutually Non-Exclusive Classes M Soliński, M Lepek, A Pater, K Muter, P Wiszniewski, D Kokosińska, ... 2020 Computing in Cardiology, 1-4, 2020 | 3 | 2020 |
| How initial condition impacts aggregation – a systematic numerical study M Łepek arXiv preprint arXiv:2112.14828, 2021 | 1 | 2021 |
| Computer methods for ITER–like materials LIBS diagnostics M Łepek, P Gąsior Photonics Applications in Astronomy, Communications, Industry, and High …, 2014 | 1 | 2014 |
| Towards fractal origins of the community structure in complex networks: a model-based approach M Samsel, K Makulski, M Łepek, A Fronczak, P Fronczak arXiv preprint arXiv:2309.11126, 2023 | | 2023 |
| Deep learning algorithm for visual quality assessment of the spirograms D Waląg, M Soliński, Ł Kołtowski, K Górska, P Korczyński, ... Physiological Measurement 44 (8), 085004, 2023 | | 2023 |
| FEV1/FVC but Not PEF Predicts Exacerbation Events in Daily Home Spirometry-a Pilot Study M Solinski, L Koltowski, M Lepek TP20. TP020 TELEHEALTH AND REMOTE MONITORING FOR PULMONARY, CRITICAL CARE …, 2021 | | 2021 |
| The application of artificial neural networks for laser-induced breakdown spectroscopy MP Łepek Zakład Półprzewodników, 2015 | | 2015 |
| Coagulating systems revisited with combinatorial approach–possibilities and issues M Łepek | | |
| Machine learning in medicine: an algorithm for automatic 12-lead ECG classification. M Soliński, M Łepek, D Kokosińska, J Salamon, K Muter, A Pater, Z Puzio, ... | | |
Mateusz SolińskiFaculty of Life Sciences & Medicine, King's College LondonVerified email at kcl.ac.uk
