Franz MJ Pfister
Franz MJ Pfister
Data Science, LMU
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Zitiert von
Zitiert von
Data augmentation of wearable sensor data for parkinson’s disease monitoring using convolutional neural networks
TT Um, FMJ Pfister, D Pichler, S Endo, M Lang, S Hirche, U Fietzek, ...
Proceedings of the 19th ACM international conference on multimodal …, 2017
Multiparametric optical analysis of mitochondrial redox signals during neuronal physiology and pathology in vivo
MO Breckwoldt, FMJ Pfister, PM Bradley, P Marinković, PR Williams, ...
Nature medicine 20 (5), 555-560, 2014
High-resolution motor state detection in Parkinson’s disease using convolutional neural networks
FMJ Pfister, TT Um, DC Pichler, J Goschenhofer, K Abedinpour, M Lang, ...
Scientific reports 10 (1), 5860, 2020
Blockchain-enabled clinical study consent management
HH Jung, FMJ Pfister
Technology Innovation Management Review 10 (2), 2020
Self-supervised out-of-distribution detection in brain CT scans
AR Venkatakrishnan, ST Kim, R Eisawy, F Pfister, N Navab
arXiv preprint arXiv:2011.05428, 2020
Wearable-based parkinson’s disease severity monitoring using deep learning
J Goschenhofer, FMJ Pfister, KA Yuksel, B Bischl, U Fietzek, J Thomas
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
A multi-layer Gaussian process for motor symptom estimation in people with Parkinson's disease
M Lang, FMJ Pfister, J Fröhner, K Abedinpour, D Pichler, U Fietzek, ...
IEEE Transactions on Biomedical Engineering 66 (11), 3038-3049, 2019
Parkinson's disease assessment from a wrist-worn wearable sensor in free-living conditions: Deep ensemble learning and visualization
TT Um, FMJ Pfister, DC Pichler, S Endo, M Lang, S Hirche, U Fietzek, ...
arXiv preprint arXiv:1808.02870, 2018
Glowin: A flow-based invertible generative framework for learning disentangled feature representations in medical images
A Sankar, M Keicher, R Eisawy, A Parida, F Pfister, ST Kim, N Navab
arXiv preprint arXiv:2103.10868, 2021
Voice analysis to differentiate the dopaminergic response in people with Parkinson's disease
A Jain, K Abedinpour, O Polat, MM Çalışkan, A Asaei, FMJ Pfister, ...
Frontiers in human neuroscience 15, 667997, 2021
Faster and better: how anomaly detection can accelerate and improve reporting of head computed tomography
T Finck, J Moosbauer, M Probst, S Schlaeger, M Schuberth, D Schinz, ...
Diagnostics 12 (2), 452, 2022
Automated pathology detection and patient triage in routinely acquired head computed tomography scans
T Finck, D Schinz, L Grundl, R Eisawy, M Yigitsoy, J Moosbauer, F Pfister, ...
Investigative Radiology 56 (9), 571-578, 2021
Parkinson's Disease Assessment from a Wrist-Worn Wearable Sensor in Free-Living Conditions: Deep Ensemble Learning and Visualization
T Taewoong Um, FMJ Pfister, DC Pichler, S Endo, M Lang, S Hirche, ...
arXiv e-prints, arXiv: 1808.02870, 2018
Automated Detection of Ischemic Stroke and Subsequent Patient Triage in Routinely Acquired Head CT
T Finck, D Schinz, L Grundl, R Eisawy, M Yiğitsoy, J Moosbauer, ...
Clinical Neuroradiology 32 (2), 419-426, 2022
Time for change–closing the loop in Parkinson’s Disease
FMJ Pfister, AO Ceballos-Baumann, UM Fietzek
Basal Ganglia 4 (6), 191, 2016
Dynamics-based estimation of Parkinson's disease severity using Gaussian Processes
S Endo, FJ Pfister, J Fröhner, U Fietzek, D Pichler, K Abedinpour, TT Um, ...
Second IFAC Conference on Cyber-Physical & Human Systems, 2018
Long-term detection of motor fluctuations by wrist-worn sensors in Parkinson's disease
D Pichler, U Fietzek, F Pfister, A Ahmadi, F Achilles, K Abedinpour, ...
Basal Ganglia 8, 22, 2017
Deep Learning in Objective Classification of Spontaneous Movement of Patients with Parkinson’s Disease Using Large-Scale Free-Living Sensor Data
F Pfister, D Kulić, T Um, D Pichler, A Ahmadi, M Lang, G König, F Achilles, ...
Technique for generating a medical report
F Pfister, S Byas
US Patent App. 18/031,648, 2023
RAISE--Radiology AI Safety, an End-to-end lifecycle approach
MJ Cardoso, J Moosbauer, TS Cook, BS Erdal, B Genereaux, V Gupta, ...
arXiv preprint arXiv:2311.14570, 2023
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