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Abigail Green-Saxena
Abigail Green-Saxena
Verified email at alumni.caltech.edu
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Cited by
Year
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial
H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ...
Computers in biology and medicine 124, 103949, 2020
1472020
Extensive exchange of fungal cultivars between sympatric species of fungus‐growing ants
AM Green, UG Mueller, RMM Adams
Molecular Ecology 11 (2), 191-195, 2002
1282002
Heavy water and 15N labelling with NanoSIMS analysis reveals growth rate‐dependent metabolic heterogeneity in chemostats
SH Kopf, SE McGlynn, A Green‐Saxena, Y Guan, DK Newman, ...
Environmental microbiology 17 (7), 2542-2556, 2015
932015
Patterns of 15N assimilation and growth of methanotrophic ANME‐2 archaea and sulfate‐reducing bacteria within structured syntrophic consortia revealed by FISH …
VJ Orphan, KA Turk, AM Green, CH House
Environmental microbiology 11 (7), 1777-1791, 2009
932009
Global Molecular Analyses of Methane Metabolism in Methanotrophic Alphaproteobacterium, Methylosinus trichosporium OB3b. Part II. Metabolomics and 13C …
S Yang, JB Matsen, M Konopka, A Green-Saxena, J Clubb, M Sadilek, ...
Frontiers in microbiology 4, 70, 2013
832013
Garden sharing and garden stealing in fungus-growing ants
RMM Adams, UG Mueller, AK Holloway, AM Green, J Narozniak
Naturwissenschaften 87, 491-493, 2000
832000
Supervised machine learning for the early prediction of acute respiratory distress syndrome (ARDS)
S Le, E Pellegrini, A Green-Saxena, C Summers, J Hoffman, J Calvert, ...
Journal of Critical Care 60, 96-102, 2020
752020
Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study
L Ryan, C Lam, S Mataraso, A Allen, A Green-Saxena, E Pellegrini, ...
Annals of Medicine and Surgery 59, 207-216, 2020
752020
Nitrate-based niche differentiation by distinct sulfate-reducing bacteria involved in the anaerobic oxidation of methane
A Green-Saxena, AE Dekas, NF Dalleska, VJ Orphan
The ISME journal 8 (1), 150-163, 2014
732014
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data …
H Burdick, E Pino, D Gabel-Comeau, A McCoy, C Gu, J Roberts, S Le, ...
BMJ health & care informatics 27 (1), 2020
602020
Neural crest and cancer: Divergent travelers on similar paths
KL Gallik, RW Treffy, LM Nacke, K Ahsan, M Rocha, A Green-Saxena, ...
Mechanisms of development 148, 89-99, 2017
582017
Widespread nitrogen fixation in sediments from diverse deep‐sea sites of elevated carbon loading
AE Dekas, DA Fike, GL Chadwick, A Green‐Saxena, J Fortney, ...
Environmental microbiology 20 (12), 4281-4296, 2018
482018
Prediction of diabetic kidney disease with machine learning algorithms, upon the initial diagnosis of type 2 diabetes mellitus
A Allen, Z Iqbal, A Green-Saxena, M Hurtado, J Hoffman, Q Mao, R Das
BMJ Open Diabetes Research and Care 10 (1), e002560, 2022
422022
A racially unbiased, machine learning approach to prediction of mortality: algorithm development study
A Allen, S Mataraso, A Siefkas, H Burdick, G Braden, RP Dellinger, ...
JMIR public health and surveillance 6 (4), e22400, 2020
422020
Pseudofossils in relict methane seep carbonates resemble endemic microbial consortia
JV Bailey, TD Raub, AN Meckler, BK Harrison, TMD Raub, AM Green, ...
Palaeogeography, Palaeoclimatology, Palaeoecology 285 (1-2), 131-142, 2010
342010
Convolutional neural network model for intensive care unit acute kidney injury prediction
S Le, A Allen, J Calvert, PM Palevsky, G Braden, S Patel, E Pellegrini, ...
Kidney international reports 6 (5), 1289-1298, 2021
322021
A machine learning approach to predict deep venous thrombosis among hospitalized patients
L Ryan, S Mataraso, A Siefkas, E Pellegrini, G Barnes, A Green-Saxena, ...
Clinical and Applied Thrombosis/Hemostasis 27, 1076029621991185, 2021
282021
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from …
H Burdick, E Pino, D Gabel-Comeau, C Gu, J Roberts, S Le, J Slote, ...
BMC medical informatics and decision making 20, 1-10, 2020
272020
Active sulfur cycling by diverse mesophilic and thermophilic microorganisms in terrestrial mud volcanoes of A zerbaijan
A Green‐Saxena, A Feyzullayev, CRJ Hubert, J Kallmeyer, M Krüger, ...
Environmental Microbiology 14 (12), 3271-3286, 2012
272012
Correlation of population SARS-CoV-2 cycle threshold values to local disease dynamics: exploratory observational study
CF Tso, A Garikipati, A Green-Saxena, Q Mao, R Das
JMIR public health and surveillance 7 (6), e28265, 2021
262021
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