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Jana Fehr
Jana Fehr
Berlin Institute of Health at Charité
在 bih-charite.de 的电子邮件经过验证
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引用次数
引用次数
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Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures
A Imle, P Kumberger, ND Schnellbächer, J Fehr, P Carrillo-Bustamante, ...
Nature communications 10 (1), 2144, 2019
722019
Ml4h auditing: From paper to practice
L Oala, J Fehr, L Gilli, P Balachandran, AW Leite, S Calderon-Ramirez, ...
Machine learning for health, 280-317, 2020
54*2020
Machine learning for health: algorithm auditing & quality control
L Oala, AG Murchison, P Balachandran, S Choudhary, J Fehr, AW Leite, ...
Journal of medical systems 45, 1-8, 2021
482021
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa
J Fehr, S Konigorski, S Olivier, R Gunda, A Surujdeen, D Gareta, T Smit, ...
NPJ digital medicine 4 (1), 106, 2021
412021
Piloting a survey-based assessment of transparency and trustworthiness with three medical AI tools
J Fehr, G Jaramillo-Gutierrez, L Oala, MI Gröschel, M Bierwirth, ...
Healthcare 10 (10), 1923, 2022
72022
CAD4TB software updates: different triaging thresholds require caution by users and regulation by authorities
J Fehr, R Gunda, MJ Siedner, W Hanekom, A Grant, C Lippert, EB Wong
The International Journal of Tuberculosis and Lung Disease 27 (2), 157-160, 2023
52023
A causal framework for assessing the transportability of clinical prediction models
J Fehr, M Piccininni, T Kurth, S Konigorski
medRxiv, 2022.03. 01.22271617, 2022
42022
A Trustworthy AI Reality-Check: The Lack of Transparency of Artificial Intelligence Products in Healthcare
J Fehr, B Citro, R Malpani, C Lippert, VI Madai
Frontiers in Digital Health 6, 1267290, 2024
22024
Assessing the transportability of clinical prediction models for cognitive impairment using causal models
J Fehr, M Piccininni, T Kurth, S Konigorski
BMC Medical Research Methodology 23 (1), 187, 2023
22023
Similar performances but markedly different triaging thresholds in three CAD4TB versions risk systematic errors in TB screening programs
J Fehr, EB Wong
medRxiv, 2022.04. 29.22274472, 2022
12022
Simultaneous alleviation of verification and reference standard biases in a community-based tuberculosis screening study using Bayesian latent class analysis
AK Keter, F Vanobberghen, L Lynen, A Van Heerden, J Fehr, S Olivier, ...
Plos one 19 (6), e0305126, 2024
2024
The unmet promise of trustworthy AI in healthcare: why we fail at clinical translation
VK Bürger, J Amann, CKT Bui, J Fehr, VI Madai
Frontiers in Digital Health 6, 1279629, 2024
2024
Simulating rigid head motion artifacts on brain magnitude MRI data–Outcome on image quality and segmentation of the cerebral cortex
H Olsson, JM Millward, L Starke, T Gladytz, T Klein, J Fehr, WC Lai, ...
Plos one 19 (4), e0301132, 2024
2024
Heterogeneous Medical Data Integration with Multi-Source StyleGAN
WC Lai, M Kirchler, H Yassin, J Fehr, A Rakowski, H Olsson, L Starke, ...
Medical Imaging with Deep Learning, 2024
2024
7 Data Science für Digitale Medizin
J Fehr, S Konigorski, C Lippert
Digitale Medizin: Kompendium für Studium und Praxis. Mit einem Geleitwort …, 2020
2020
Evaluating Age-Related Anatomical Consistency in Synthetic Brain MRI against Real-World Alzheimer's Disease Data.
H Yassin, J Fehr, WC Lai, A Krichevsky, A Rakowski, C Lippert
Medical Imaging with Deep Learning, 0
Characterizing inflammation in sub-clinical TB disease
L Ndlovu, J Fehr, T Zulu, S Olivier, D Gareta, K Baisley, T Ndung’u, ...
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