Publications MSc R. Ricci Lopes
- Positions
- PhD Candidate, Other Academic Staff
- Main activities
- Education, Research
- Specialisation
- Machine Learning
- Focus of research
Aortic stenosis (AS) is one of the most common valvular heart disease, impacting in general the elderly population. The treatment is consistent in the implantation of a new aortic valve, which can be done through open-heart surgery, or using a catheter for the deployment of a new valve, like the transcatheter aortic valve implantation (TAVI). Although the TAVI procedure is indicated, there are not many public data about TAVI candidates or patients. in the first year after the procedure.
In this project our focus is on combining clinical data and clinical data with image data using machine learning approaches such as Convolutional Neural Networks in order to predict the post-procedure symptoms improvement and the mortality.
Amsterdam UMC Research Institutes
AMC departments
All publications
2021
- Bleijendaal Hidde, Ramos Lucas A, Lopes Ricardo R, Verstraelen Tom E, Baalman Sarah W E, Oudkerk Pool Marinka D, Tjong Fleur V Y, Melgarejo-Meseguer Francisco M, Gimeno-Blanes F Javier, Gimeno-Blanes Juan R, Amin Ahmad S, Winter Michiel M, Marquering Henk A, Kok Wouter E M, Zwinderman Aeilko H, Wilde Arthur A M, Pinto Yigal M Computer versus cardiologist: Is a machine learning algorithm able to outperform an expert in diagnosing a phospholamban p.Arg14del mutation on the electrocardiogram? Heart rhythm 2021;18 (1):79-87 [PubMed]
2020
- Lopes Ricardo R., Mamprin Marco, Zelis Jo M., Tonino Pim A. L., van Mourik Martijn S., Vis Marije M., Zinger Sveta, de Mol Bas A. J. M., de With Peter H. N., Marquering Henk A. Inter-center cross-validation and finetuning without patient data sharing for predicting transcatheter aortic valve implantation outcomein: Alba Garcia Seco de Herrera, Alejandro Rodriguez Gonzalez, KC Santosh, Zelalem Temesgen, Bridget Kane, Paolo Soda, editors. Proceedings - 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems, CBMS 2020. Institute of Electrical and Electronics Engineers Inc.; 2020. p. 591-596
2019
- Lopes R. R., van Mourik M. S., Schaft E. V., Ramos L. A., Baan Jr J., Vendrik J., de Mol B. A. J. M., Vis M. M., Marquering H. A. Value of machine learning in predicting TAVI outcomes Netherlands heart journal 2019;27 (9):443-450 [PubMed]
2017
- Pereira Clayton R., Passos Leandro A., Lopes Ricardo R., Weber Silke A.T., Hook Christian, Papa João Paulo Parkinson’s disease identification using restricted Boltzmann machinesin: Anders Heyden, Michael Felsberg, Norbert Kruger, editors. Computer Analysis of Images and Patterns - 17th International Conference, CAIP 2017, Proceedings. Springer Verlag; 2017. p. 70-80, ISBN 9783319646978
2016
- Lopes Ricardo, Costa Kelton, Papa João On the evaluation of tensor-based representations for optimum-path forest classificationin: Friedhelm Schwenker, Hazem M. Abbas, Neamat El Gayar, Edmondo Trentin, editors. Artificial Neural Networks in Pattern Recognition - 7th IAPR TC3 Workshop, ANNPR 2016, Proceedings. Springer Verlag; 2016. p. 117-125, ISBN 9783319461816