Author

D. Remondini

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Organism:E. coli· 1 Organism:human· 1 Assay:imaging· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

B. A. Pataki· 1 shared B. C. L. van der Putten· 1 shared C. Schultsz· 1 shared COMPARE ML-AMR group· 1 shared D. Aytan-Aktug· 1 shared E. Giampieri· 1 shared F. W. Asselbergs· 1 shared G. Castellani· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperMicrobiology

B. A. Pataki

Mutual co-authors in cluster

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2 papers

Recent·Most cited

Prediction of vascular ageing based on smartphone acquired PPG signals

L. Dall'Olio, N. Curti, D. Remondini, Y. S. Harb, F. W. Asselbergs, G. Castellani, H.-W. Uh

This study uses machine learning and deep learning to predict vascular aging from smartphone-acquired PPG signals, achieving high accuracy with both approaches.

bioRxiv · May 26, 2020Biophysics

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

B. A. Pataki, S. Matamoros, B. C. L. van der Putten, D. Remondini, E. Giampieri, D. Aytan-Aktug, R. S. Hendriksen, O. Lund, I. Csabai, C. Schultsz, COMPARE ML-AMR group

This paper predicts ciprofloxacin minimum inhibitory concentration in Escherichia coli using machine learning based on genome-wide mutation profiles and antimicrobial resistance gene presence.

bioRxiv · Jan 17, 2020Microbiology