Artikel mit Open-Access-Mandaten - Nasim KatebiWeitere Informationen
Verfügbar: 9
Improving the quality of point of care diagnostics with real-time machine learning in low literacy LMIC settings
CE Valderrama, F Marzbanrad, L Stroux, B Martinez, R Hall-Clifford, C Liu, ...
Proceedings of the 1st ACM SIGCAS Conference on Computing and Sustainable …, 2018
Mandate: US National Institutes of Health
An open source autocorrelation-based method for fetal heart rate estimation from one-dimensional Doppler ultrasound
CE Valderrama, L Stroux, N Katebi, E Paljug, R Hall-Clifford, P Rohloff, ...
Physiological measurement 40 (2), 025005, 2019
Mandate: US National Institutes of Health, UK Research & Innovation
A review of fetal cardiac monitoring, with a focus on low-and middle-income countries
CE Valderrama, N Ketabi, F Marzbanrad, P Rohloff, GD Clifford
Physiological measurement 41 (11), 11TR01, 2020
Mandate: US National Institutes of Health
CNN-based LCD transcription of blood pressure from a mobile phone camera
SS Kulkarni, N Katebi, CE Valderrama, P Rohloff, GD Clifford
Frontiers in Artificial Intelligence 4, 543176, 2021
Mandate: US National Science Foundation, US National Institutes of Health
Unsupervised hidden semi-Markov model for automatic beat onset detection in 1D Doppler ultrasound
N Katebi, F Marzbanrad, L Stroux, CE Valderrama, GD Clifford
Physiological measurement 41 (8), 085007, 2020
Mandate: US National Institutes of Health, UK Research & Innovation
Hierarchical attentive network for gestational age estimation in low-resource settings
N Katebi, R Sameni, P Rohloff, GD Clifford
IEEE journal of biomedical and health informatics 27 (5), 2501-2511, 2023
Mandate: US National Institutes of Health
Deep sequence learning for assessing hypertension in pregnancy from Doppler signals
N Katebi, GD Clifford
medRxiv, 2022.01. 26.22269921, 2022
Mandate: Bill & Melinda Gates Foundation, US National Institutes of Health, Gordon …
Deep Sequence Learning for Accurate Gestational Age Estimation from a $25 Doppler Device
N Katebi, R Sameni, GD Clifford
Neurips Workshop, 2020
Mandate: US National Institutes of Health
Advancing Fetal Surveillance with Physiological Sensing: Detecting Hypoxia in Fetal Sheep
W Tang, N Tran, N Katebi, R Sameni, GD Clifford, D Walker, V Horlali, ...
2024 IEEE SENSORS, 1-4, 2024
Mandate: National Health and Medical Research Council, Australia
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