| 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 | 112 | 2002 |
| Garden sharing and garden stealing in fungus-growing ants RMM Adams, UG Mueller, AK Holloway, AM Green, J Narozniak Naturwissenschaften 87 (11), 491-493, 2000 | 72 | 2000 |
| 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 | 70 | 2009 |
| 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 | 66 | 2015 |
| Global molecular analyses of methane metabolism in methanotrophic Alphaproteobacterium, Methylosinus trichosporium OB3b. Part II. Metabolomics and 13C-labeling study MG Kalyuzhanaya, S Yang, JB Matsen, M Konopka, A Green-Saxena, ... Frontiers in microbiology 4, 70, 2013 | 56 | 2013 |
| 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 | 50 | 2014 |
| 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 | 26 | 2010 |
| 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 | 25 | 2017 |
| 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 | 17 | 2012 |
| 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 | 14 | 2018 |
| Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction H Mohamadlou, S Panchavati, J Calvert, A Lynn-Palevsky, S Le, A Allen, ... Health informatics journal 26 (3), 1912-1925, 2020 | 6 | 2020 |
| 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 | 5 | 2020 |
| 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), e100109, 2020 | 5 | 2020 |
| Chapter two—whole cell immunomagnetic enrichment of environmental microbial consortia using rRNATargeted Magneto-FISH E Trembath-Reichert, A Green-Saxena, VJ Orphan, FD Edward Microbial metagenomics, metatranscriptomics, and metaproteomics, 21-44, 2013 | 5 | 2013 |
| Whole cell immunomagnetic enrichment of environmental microbial consortia using rRNA-targeted Magneto-FISH E Trembath-Reichert, A Green-Saxena, VJ Orphan Methods in Enzymology 531, 21-44, 2013 | 5 | 2013 |
| 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, ... medRxiv, 2020 | 2 | 2020 |
| 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 | 1 | 2020 |
| Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ... Journal of clinical medicine 9 (12), 3834, 2020 | | 2020 |
| 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), 1-10, 2020 | | 2020 |
| Predicting Ventilator-Associated Pneumonia with Machine Learning C Giang, J Calvert, G Barnes, A Siefkas, A Green-Saxena, J Hoffman, ... | | 2020 |
Rachelle M.M. AdamsThe Ohio State UniversityGeverifieerd e-mailadres voor osu.edu
