Authors: Wilson, Rory P, Holton, Mark D, di Virgilio, Agustina, Williams, Hannah, Shepard, Emily L C, Lambertucci, Sergio, Quintana, Flavio, Sala, Juan E, Balaji, Bharathan, Lee, Eun Sun, Srivastava, Mani, Scantlebury, D Michael, Duarte, Carlos M
Subject Terms: behaviour identification, machine learning, LoCoD, accelerometry, biologging
Relation: http://hdl.handle.net/10255/dryad.187391
Authors: Ryo, Masahiro, Yoshimura, Chihiro, Iwasaki, Yuichi
Subject Terms: machine learning, river, flow regime
Subject Geographic: Sagami River, Japan
Time: 1993-1999
Relation: http://hdl.handle.net/10255/dryad.150552
Authors: Schatz, Annakate M, Kramer, Andrew M, Drake, John M
Subject Terms: species distribution model, Batrachochytrium dendrobatidis, machine learning, hindcasting
Relation: http://hdl.handle.net/10255/dryad.139432
Authors: Folmer, Eelke O., van Beusekom, Justus E. E., Dolch, Tobias, Gräwe, Ulf, van Katwijk, Marieke M., Kolbe, Kerstin, Philippart, Catharina J. M.
Subject Terms: Boyce index, Habitat Distribution Model, Machine Learning, Habitat Management, Model Transferability, Ensemble Forecasting, seagrass
Subject Geographic: North Sea, Netherlands, Germany, Denmark
Time: Wadden Sea
Relation: http://hdl.handle.net/10255/dryad.123260
Authors: Folmer, Eelke O., van Beusekom, Justus E. E., Dolch, Tobias, Gräwe, Ulf, van Katwijk, Marieke M., Kolbe, Kerstin, Philippart, Catharina J. M.
Subject Terms: Boyce index, Habitat Distribution Model, Machine Learning, Habitat Management, Model Transferability, Ensemble Forecasting, seagrass
Subject Geographic: North Sea, Netherlands, Germany, Denmark
Time: Wadden Sea
Relation: http://hdl.handle.net/10255/dryad.123261
Authors: Folmer, Eelke O., van Beusekom, Justus E. E., Dolch, Tobias, Gräwe, Ulf, van Katwijk, Marieke M., Kolbe, Kerstin, Philippart, Catharina J. M.
Subject Terms: Boyce index, Habitat Distribution Model, Machine Learning, Habitat Management, Model Transferability, Ensemble Forecasting, seagrass
Subject Geographic: North Sea, Netherlands, Germany, Denmark
Time: Wadden Sea
Relation: http://hdl.handle.net/10255/dryad.123259
Authors: Scholes, Chris, McGraw, Paul V., Nyström, Marcus, Roach, Neil W.
Subject Terms: Microsaccades, Fixational saccades, Contrast Sensitivity, Machine Learning
Relation: http://hdl.handle.net/10255/dryad.97850
Subject Terms: Active Machine Learning, Supervised Machine Learning, Natural Language Processing, Medical Informatics, Drug Interactions, Clinical Medicine
Relation: Vasilakes J, Rizvi R, Melton GB, Pakhomov S, Zhang R (2018) Evaluating active learning methods for annotating semantic predications. JAMIA Open 1(2): 275-282.; http://hdl.handle.net/10255/dryad.181588
Authors: Ezray, Briana, Wham, Drew, Hill, Carrie, Hines, Heather
Subject Terms: Müllerian mimicry, biogeography, convolutional neural network, machine learning, coloration
Subject Geographic: United States
Relation: http://hdl.handle.net/10255/dryad.226679
Subject Terms: magnetometer, behaviour recognition, biomechanics, machine learning, angular velocity, Earth's magnetic field, accelerometer, meerkats
Subject Geographic: Kalahari Desert, Namib Desert
Relation: Chakravarty P, Maalberg M, Cozzi G, Ozgul A, Aminian K (2019) Behavioural compass: animal behaviour recognition using magnetometers. Movement Ecology 7(1): 28.; http://hdl.handle.net/10255/dryad.224636
Authors: Viswanath, Satish E., Chirra, Prathyush V., Yim, Michael C., Rofsky, Neil M., Purysko, Andrei S., Rosen, Mark A., Bloch, Nicolas B., Madabhushi, Anant
Subject Terms: radiomics, classifiers, machine learning, comparison
Relation: Viswanath SE, Chirra PV, Yim MC, Rofsky NM, Purysko AS, Rosen MA, Bloch NB, Madabhushi A (2019) Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study. BMC Medical Imaging 19:22.; http://hdl.handle.net/10255/dryad.203329
Authors: Sullivan, Jack, Smith, Megan L., Espindola, Anahi, Ruffley, Megan, Rankin, Andrew, Tank, David, Carstens, Bryan
Subject Terms: Comparative Phylogeography, Random Forest, Machine Learning, Cryptic Diversity
Subject Geographic: Pacific Northwest
Relation: Sullivan J, Smith ML, Espíndola A, Ruffley M, Rankin A, Tank D, Carstens B (2019) Integrating life history traits into predictive phylogeography. Molecular Ecology.; http://hdl.handle.net/10255/dryad.203055
Authors: Guan, Meijian, Cho, Samuel, Petro, Robin, Zhang, Wei, Pasche, Boris, Topaloglu, Umit
Subject Terms: Machine Learning, Natural language processing, Electronic Health Records, Cancer, Genomics
Relation: Guan M, Cho S, Petro R, Zhang W, Pasche B, Topaloglu U (2019) Natural language processing and recurrent network models for identifying genomic mutation-associated cancer treatment change from patient progress notes. JAMIA Open 2(1): 139-149.; http://hdl.handle.net/10255/dryad.201773
Authors: Sun, Xudong, Liu, Junbin, Zhu, Ke, Hu, Jun, Jiang, Xiaogang, Liu, Yande
Subject Terms: terahertz spectroscopy, food additive, machine learning, quantitative analysis
Relation: Sun X, Liu J, Zhu K, Hu J, Jiang X, Liu Y (2019) Generalized regression neural network association with terahertz spectroscopy for quantitative analysis of benzoic acid additive in wheat flour. Royal Society Open Science 6(7): 190485.; http://hdl.handle.net/10255/dryad.221358
Availability:
https://doi.org/10.5061/dryad.945c410
https://doi.org/10.5061/dryad.945c410/1
https://doi.org/10.5061/dryad.945c410/2
https://doi.org/10.5061/dryad.945c410/3
https://doi.org/10.5061/dryad.945c410/4
https://doi.org/10.5061/dryad.945c410/5
https://doi.org/10.5061/dryad.945c410/6
https://doi.org/10.5061/dryad.945c410/7
https://doi.org/10.5061/dryad.945c410/8
https://doi.org/10.1098/rsos.190485
Authors: Suvorov, Anton, Hochuli, Joshua, Schrider, Daniel
Subject Terms: supervised machine learning, convolutional neuronal network, phylogenetics
Relation: http://hdl.handle.net/10255/dryad.219973
Availability:
https://doi.org/10.5061/dryad.ct2895s
https://doi.org/10.5061/dryad.ct2895s/1
https://doi.org/10.5061/dryad.ct2895s/2
https://doi.org/10.5061/dryad.ct2895s/3
https://doi.org/10.5061/dryad.ct2895s/4
https://doi.org/10.5061/dryad.ct2895s/5
https://doi.org/10.5061/dryad.ct2895s/6
https://doi.org/10.5061/dryad.ct2895s/7
https://doi.org/10.5061/dryad.ct2895s/8
https://doi.org/10.5061/dryad.ct2895s/9
Authors: Spiro, Adam, Fernández García, Jonatan, Yanover, Chen
Subject Terms: Machine Learning, Medical Informatics, MeSH Headings, Adverse Drug Reaction, Drug Repositioning, Literature Based Discovery
Relation: Spiro A, Fernández García J, Yanover C (2019) Inferring new relations between medical entities using literature curated term co-occurrences. JAMIA Open.; http://hdl.handle.net/10255/dryad.219222
Authors: Hoyal Cuthill, Jennifer F., Guttenberg, Nicholas, Ledger, Sophie, Crowther, Robyn, Huertas, Blanca
Subject Terms: machine learning, deep learning, AI, evolution, mimicry, evolutionary convergence, coevolution
Subject Geographic: South America, Central America, North America
Relation: Hoyal Cuthill JF, Guttenberg N, Ledger S, Crowther R, Huertas B (2019) Deep learning on butterfly phenotypes tests evolution’s oldest mathematical model. Science Advances 5(8): eaaw4967.; http://hdl.handle.net/10255/dryad.217276
Authors: Stacher Hörndli, Cornelia N, Wong, Eleanor, Ferris, Elliott, Bennett, Kathleen, Steinwand, Susan, Rhodes, Alexis Nikole, Fletcher, P. Thomas, Gregg, Christopher
Subject Terms: machine learning, behavior, foraging, behavioral genetics
Relation: Stacher Hörndli CN, Wong E, Ferris E, Bennett K, Steinwand S, Rhodes AN, Fletcher PT, Gregg C (2019) Complex economic behavior patterns are constructed from finite, genetically controlled modules of behavior. Cell Reports 28(7): 1814-1829.e6.; http://hdl.handle.net/10255/dryad.215906
Subject Terms: Active Machine Learning, Supervised Machine Learning, Natural Language Processing, Medical Informatics, Drug Interactions, Clinical Medicine
Relation: http://hdl.handle.net/10255/dryad.181589
Authors: Ezray, Briana, Wham, Drew, Hill, Carrie, Hines, Heather
Subject Terms: Müllerian mimicry, Bombus, biogeography, convolutional neural network, machine learning, coloration
Subject Geographic: United States
Relation: http://hdl.handle.net/10255/dryad.226750