Michael Moor
Michael Moor
MD, PhD. Postdoctoral researcher at Stanford University, Department of Computer Science.
Verified email at - Homepage
Cited by
Cited by
Foundation models for generalist medical artificial intelligence
M Moor, O Banerjee, ZSH Abad, HM Krumholz, J Leskovec, EJ Topol, ...
Nature 616 (7956), 259-265, 2023
Early prediction of circulatory failure in the intensive care unit using machine learning
SL Hyland, M Faltys, M Hüser, X Lyu, T Gumbsch, C Esteban, C Bock, ...
Nature Medicine 26 (3), 364-373, 2020
A survey of topological machine learning methods
F Hensel, M Moor, B Rieck
Frontiers in Artificial Intelligence 4, 681108, 2021
Topological Autoencoders
M Moor, M Horn, B Rieck, K Borgwardt
International Conference on Machine Learning (ICML), 7045--7054, 2020
Accelerating detection of lung pathologies with explainable ultrasound image analysis
J Born, N Wiedemann, M Cossio, C Buhre, G Brändle, K Leidermann, ...
Applied Sciences 11 (2), 672, 2021
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
B Rieck, M Togninalli, C Bock, M Moor, M Horn, T Gumbsch, K Borgwardt
International Conference on Learning Representations (ICLR), 2019., 2018
Set Functions for Time Series
M Horn, M Moor, C Bock, B Rieck, K Borgwardt
International Conference on Machine Learning (ICML), 4353-4363, 2020
Early prediction of sepsis in the ICU using machine learning: a systematic review
M Moor, B Rieck, M Horn, CR Jutzeler, K Borgwardt
Frontiers in medicine 8, 348, 2021
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
M Moor, M Horn, B Rieck, D Roqueiro, K Borgwardt
Proceedings of the 4th Machine Learning for Healthcare Conference, 2019., 2019
Med-Flamingo: a Multimodal Medical Few-shot Learner
M Moor, Q Huang, S Wu, M Yasunaga, C Zakka, Y Dalmia, EP Reis, ...
Accepted to ML4H 2023, 2023
Topological Graph Neural Networks
M Horn, E De Brouwer, M Moor, Y Moreau, B Rieck, K Borgwardt
International Conference on Learning Representations (ICLR), 2022, 2022
Almanac: Retrieval-Augmented Language Models for Clinical Medicine
C Zakka, A Chaurasia, R Shad, A Dalal, J Kim, M Moor, K Alexander, ...
NEJM AI, 2023
Association mapping in biomedical time series via statistically significant shapelet mining
C Bock, T Gumbsch, M Moor, B Rieck, D Roqueiro, K Borgwardt
Bioinformatics 34 (13), i438-i446, 2018
Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning
C Bock, M Moor, CR Jutzeler, K Borgwardt
Artificial Neural Networks, 33-71, 2020
Quantification of liver, subcutaneous, and visceral adipose tissues by MRI before and after bariatric surgery
AC Meyer-Gerspach, R Peterli, M Moor, P Madörin, A Schötzau, D Nabers, ...
Obesity surgery 29, 2795-2805, 2019
Predicting sepsis using deep learning across international sites: a retrospective development and validation study
M Moor, N Bennett, D Plečko, M Horn, B Rieck, N Meinshausen, ...
The Lancet's eClinicalMedicine 62, 102124, 2023
Path Imputation Strategies for Signature Models
M Moor, M Horn, C Bock, K Borgwardt, B Rieck
ICML 2020 Workshop on the Art of Learning with Missing Values (Artemiss), 2020
Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting
B Yan, R Liu, DE Kuo, S Adithan, EP Reis, S Kwak, VK Venugopal, ...
Accepted at Findings of EMNLP 2023., 2023
Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients
B Fan, J Klatt, M Moor, LA Daniels, LN Sanchez-Pinto, PKA Agyeman, ...
Bioinformatics 38 (Supplement_1), i101-i108, 2022
AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments
S Schmidgall, R Ziaei, C Harris, E Reis, J Jopling, M Moor
arXiv preprint arXiv:2405.07960, 2024
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