Random Forests

Cited by (1,833)

Items 901–1,000 of 1,833

1. Explainable artificial intelligence model to predict acute critical illness from electronic health records
   Lauritsen, Simon Meyer, Kristensen, Mads, Olsen, Mathias Vassard, Larsen, Morten Skaarup, Lauritsen, Katrine Meyer, Jørgensen, Marianne Johansson, Lange, Jeppe, Thiesson, Bo · 2020 · Nature Communications
2. No silver bullets in correlative ecological niche modelling: insights from testing among many potential algorithms for niche estimation
   Huijie Qiao, Jorge M. Soberón, A. Townsend Peterson · 2015 · Methods in Ecology and Evolution
3. Cancer-Specific High-Throughput Annotation of Somatic Mutations: Computational Prediction of Driver Missense Mutations
   Hannah K. Carter, Sining Chen, Leyla Işık, Svitlana Tyekucheva, Victor E. Velculescu, Kenneth W. Kinzler, Bert Vogelstein, Rachel Karchin · 2009 · Cancer Research
4. Variable selection using Mean Decrease Accuracy and Mean Decrease Gini based on Random Forest
   Hong Han, Xiaoling Guo, Yu Hua · 2016 · IEEE International Conference on Software Engineering and Service Science (ICSESS)
5. Dynamic classifier selection: Recent advances and perspectives
   Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti · 2017 · Information Fusion
6. Prediction of the development of acute kidney injury following cardiac surgery by machine learning
   Po-Yu Tseng, Yi‐Ting Chen, Chuen-Heng Wang, Kuan‐Ming Chiu, Yu-Sen Peng, Shih‐Ping Hsu, Kang-Lung Chen, Chih‐Yu Yang, Oscar Kuang‐Sheng Lee · 2020 · Critical Care
7. Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
   Essam Halim Houssein, Asmaa S.A. Hammad, Abdelmgeid Amin Ali · 2022 · Neural Computing and Applications
8. Classification with correlated features: unreliability of feature ranking and solutions
   Laura Toloşi, Thomas Lengauer · 2011 · Bioinformatics
9. Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique
   Tuan V. Vu, Zongbo Shi, Jing Cheng, Qiang Zhang, Kebin He, Shuxiao Wang, Roy M. Harrison · 2019 · Atmospheric chemistry and physics
10. Monitoring land cover change in urban and peri-urban areas using dense time stacks of Landsat satellite data and a data mining approach
    Annemarie Schneider · 2012 · Remote Sensing of Environment
11. The choice of scaling technique matters for classification performance
    Lucas Amorim, George D. C. Cavalcanti, Rafael M. O. Cruz · 2022 · Applied Soft Computing
12. Gut microbiome-wide association study of depressive symptoms
    Djawad Radjabzadeh, Jos A. Bosch, André Gerardus Uitterlinden, Aeilko Having Zwinderman, M. Arfan Ikram, Joyce B. J. van Meurs, Annemarie Ida Luik, Max Nieuwdorp, Anja Lok, Cornelia M. van Duijn et al. · 2022 · Nature Communications
13. Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data
    Andrew Thomas Hudak, Nicholas L. Crookston, Jeffrey S. Evans, David E. Hall, Michael J. Falkowski · 2008 · Remote Sensing of Environment
14. Classification of Rockburst in Underground Projects: Comparison of Ten Supervised Learning Methods
    Jian Zhou, Xibing Li, Hani S. Mitri · 2016 · Journal of Computing in Civil Engineering
15. Deep Learning-Based Image Segmentation on Multimodal Medical Imaging
    Zhe Guo, Xiang Li, Heng Huang, Ning Guo, Quanzheng Li · 2019 · IEEE Transactions on Radiation and Plasma Medical Sciences
16. Functional Carbon from Nature: Biomass‐Derived Carbon Materials and the Recent Progress of Their Applications
    Hongzhe He, Ruoqun Zhang, Pengcheng Zhang, Ping Wang, Ning Chen, Binbin Qian, Lian Zhang, Jianglong Yu, Baiqian Dai · 2023 · Advanced Science
17. Data fusion in intelligent transportation systems: Progress and challenges – A survey
    Faouzi, Nour-Eddin El, Leung, Henry, Kurian, Ajeesh · 2011 · Information Fusion
18. Using sensitivity analysis and visualization techniques to open black box data mining models
    Paulo Cesar Cortez, Mark J. Embrechts · 2012 · Information Sciences
19. A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants
    Emad Dawood Abbas Kaky, Victoria Nolan, Abdulaziz S. Alatawi, Francis S Gilbert · 2020 · Ecological Informatics
20. Stairway Plot 2: demographic history inference with folded SNP frequency spectra
    Xiaoming Liu, Yun‐Xin Fu · 2020 · Genome biology
21. Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects
    Natei Ermias Benti, Mesfin Diro Chaka, Addisu Gezahegn Semie · 2023 · Sustainability
22. The Heterogeneity Problem: Approaches to Identify Psychiatric Subtypes
    Feczko, Eric, Miranda-Dominguez, Oscar, Marr, Mollie, Graham, Alice M., Nigg, Joel T., Fair, Damien A. · 2019 · Trends in Cognitive Sciences
23. Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics
    Melanie A. Murphy, Jeffrey S. Evans, Andrew T. Storfer · 2010 · Ecology
24. Hour-ahead wind power forecast based on random forests
    Ali Lahouar, Jaleleddine Ben Hadj Slama · 2017 · Renewable Energy
25. Real time head pose estimation with random regression forests
    Gabriele Fanelli, Jüergen Gall, Luc Van Gool · 2011 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
26. Opcode sequences as representation of executables for data-mining-based unknown malware detection
    Igor Santos, Félix Brezo, Xabier Ugarte-Pedrero, Pablo G. Bringas · 2011 · Information Sciences
27. Fingerprinting food: current technologies for the detection of food adulteration and contamination
    David I. Ellis, Victoria L. Brewster, Warwick B. Dunn, James William Allwood, Alexander P. Golovanov, Royston Goodacre · 2012 · Chemical Society Reviews
28. Parsing Argumentation Structures in Persuasive Essays
    Christian Stab, Iryna Gurevych · 2017 · Computational Linguistics
29. Contrasting pathways of carbon sequestration in paddy and upland soils
    Xiangbi Chen, Yajun Hu, Yinhang Xia, Shengmeng Zheng, Chong Ma, Yichao Rui, Hongbo He, Daoyou Huang, Zhenhua Zhang, Tida Ge et al. · 2021 · Global Change Biology
30. SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification
    Manuel Tardáguila, Lorena de la Fuente, Cristina Martí, Cécile Pereira, Francisco J. Pardo-Palacios, Héctor del Risco, Marc Ferrell, Maravillas Mellado-López, Marissa G. Macchietto, Kenneth Verheggen et al. · 2018 · Genome Research
31. An up-to-date comparison of state-of-the-art classification algorithms
    Zhang, Chongsheng, Liu, Changchang, Zhang, Xiangliang, Almpanidis, George · 2017 · Expert Systems with Applications
32. From genome-wide arrays to tailor-made biomarker readout – Progress towards routine analysis of skin sensitizing chemicals with GARD
    Andy Forreryd, Kathrin Stephanie Zeller, Tim Lindberg, Henrik Johansson, Malin Lindstedt · 2016 · Toxicology in Vitro
33. Applications of XGBoost in water resources engineering: A systematic literature review (Dec 2018–May 2023)
    Majid Niazkar, Andrea Menapace, Bruno Brentan, Reza Piraei, David Antonio Jimenez Osorio, Pranav Dhawan, Maurizio Righetti · 2024 · Environmental Modelling & Software
34. High-Dimensional Variable Selection for Survival Data
    Hemant Ishwaran, Udaya B. Kogalur, Eiran Z. Gorodeski, Andy J. Minn, Michael S. Lauer · 2010 · Journal of the American Statistical Association
35. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests
    João Paulo Marôco, Dina Silva, Ana Pina Rodrigues, Manuela Guerreiro, Isabel J. Santana, Alexandre de Mendonça · 2011 · BMC Research Notes
36. Evaluating Random Forests for Survival Analysis Using Prediction Error Curves
    Ulla Brasch Mogensen, Hemant Ishwaran, Thomas Alexander Gerds · 2012 · Journal of Statistical Software
37. A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment
    Jianguo Chen, Kenli Li, Zhuo Tang, Kashif Bilal, Shui Yu, Chuliang Weng, Keqin Li · 2016 · IEEE Transactions on Parallel and Distributed Systems
38. Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques
    Sherrie Wang, George Azzari, David B. Lobell · 2019 · Remote Sensing of Environment
39. Impact of extreme weather conditions on European crop production in 2018
    Damien Beillouin, Bernhard Schauberger, Ana Bastos, Philippe Ciais, David Makowski · 2020 · Philosophical Transactions of the Royal Society B Biological Sciences
40. The Impact of Diversity on Online Ensemble Learning in the Presence of Concept Drift
    Leandro Lei Minku, A. P. White, Xin Yao · 2009 · IEEE Transactions on Knowledge and Data Engineering
41. Machine learning prediction of biochar yield and carbon contents in biochar based on biomass characteristics and pyrolysis conditions
    Xinzhe Zhu, Yinan Li, Xiaonan Wang · 2019 · Bioresource Technology
42. Machine Learning Based Intrusion Detection Systems for IoT Applications
    Abhishek Verma, Virender Ranga · 2019 · Wireless Personal Communications
43. Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions
    Katja Berger, Jochem Verrelst, Jean‐Baptiste Féret, Zhihui Wang, Matthias Wocher, Markus Strathmann, Martin Danner, Wolfram Mauser, Tobias Hank · 2020 · Remote Sensing of Environment
44. Deep learning and machine vision for food processing: A survey
    Lili Zhu, Petros Spachos, Erica Pensini, Konstantinos N. Plataniotis · 2021 · Current Research in Food Science
45. Allergy or tolerance in children sensitized to peanut: Prevalence and differentiation using component-resolved diagnostics
    Nicolaos C. Nicolaou, Maryam Poorafshar, Clare S Murray, Angela Simpson, Henric Winell, Gina Kerry, Annika Härlin, Ashley A. Woodcock, S. Ahlstedt, Adnan Čustović · 2010 · Journal of Allergy and Clinical Immunology
46. Deep learning and its application in geochemical mapping
    Renguang Zuo, Yihui Xiong, Jian Wang, Emmanuel John M. Carranza · 2019 · Earth-Science Reviews
47. Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets
    Ilya N Belevich, Merja Joensuu, Darshan Kumar, Helena Vihinen, Eija Jokitalo · 2016 · PLoS Biology
48. Land cover 2.0
    Michael A. Wulder, Nicholas C. Coops, David P. Roy, Joanne C. White, Txomin Hermosilla · 2018 · International Journal of Remote Sensing
49. Prediction of surface roughness in extrusion-based additive manufacturing with machine learning
    Zhixiong Li, Ziyang Zhang, Junchuan Shi, Dazhong Wu · 2019 · Robotics and Computer-Integrated Manufacturing
50. The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use
    Stefan Leyk, Andrea Elizabeth Gaughan, Susana B. Adamo, Alex de Sherbinin, Deborah L. Balk, Sérgio Freire, Amy Rose, Forrest Robert Stevens, Brian and Blankespoor, Charlie Frye et al. · 2019 · Earth system science data
51. Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models
    Xilei Zhao, Xiang “Jacob” Yan, Alan Yu, Pascal Van Hentenryck · 2020 · Travel Behaviour and Society
52. Real-Time Human Pose Recognition in Parts from Single Depth Images
    Jamie Shotton, Andrew W Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, Andrew Blake · 2012 · Studies in computational intelligence
53. Automated sleep stage identification system based on time–frequency analysis of a single EEG channel and random forest classifier
    Luay Fraiwan, Khaldon Y. Lweesy, Natheer Khasawneh, Heinrich Wenz, Hartmut Dickhaus · 2011 · Computer Methods and Programs in Biomedicine
54. Cancer of the esophagus and esophagogastric junction
    Thomas W. Rice, Valerie W. Rusch, Hemant Ishwaran, Eugene H. Blackstone · 2010 · Cancer
55. Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection
    Joseph J. Lim, C. Lawrence Zitnick, Piotr Dollár · 2013 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
56. Mapping the global depth to bedrock for land surface modeling
    Wei Shangguan, Tomislav Hengl A, J.S. Mendes de Jesus, Hua Yuan, Yongjiu Dai · 2016 · Journal of Advances in Modeling Earth Systems
57. cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R
    Christian Thiele, Gerrit H. F. Hirschfeld · 2021 · Journal of Statistical Software
58. Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques
    Kristof Coussement, Dirk Van den Poel · 2006 · Expert Systems with Applications
59. Chalcone Derivatives: Promising Starting Points for Drug Design
    Marcelo do Nascimento Gomes, Eugene N. Muratov, Maristela Pereira, Josana de Castro Peixoto, Lucimar Pinheiro Rosseto, Pedro Cravo, Carolina Horta Andrade, Bruno J. Neves · 2017 · Molecules
60. Machine learning approaches and databases for prediction of drug–target interaction: a survey paper
    Maryam Bagherian, Elyas Sabeti, Kai Wang, Maureen A. Sartor, Zaneta Nikolovska‐Coleska, Kayvan Najarian · 2019 · Briefings in Bioinformatics
61. Bond Risk Premia with Machine Learning
    Daniele Bianchi, Matthias Büchner, Andrea Tamoni · 2018 · Review of Financial Studies
62. Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves
    Tobias Domhan, Jost Tobias Springenberg, Frank Hutter · 2015 · FreiDok plus (Universitätsbibliothek Freiburg)
63. Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
    Liang Han, Guijun Yang, Huayang Dai, Bo Xu, Hao Frank Yang, Haikuan Feng, Zhenhai Li, Xiaodong Yang · 2019 · Plant Methods
64. Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting
    Wouter Buckinx, Dirk Van den Poel · 2004 · European Journal of Operational Research
65. Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China
    Haoyuan Hong, Paraskevas Tsangaratos, Ioanna Ilia, Junzhi Liu, A‐Xing Zhu, Wei Chen · 2017 · The Science of The Total Environment
66. Analysis of machine learning techniques for heart failure readmissions
    Mortazavi, Bobak J., Downing, Nicholas S., Bucholz, Emily M., Dharmarajan, Kumar, Manhapra, Ajay, Li, Shu-Xia, Negahban, Sahand N., Krumholz, Harlan M. · 2016 · Circulation: Cardiovascular Quality and Outcomes
67. Comparison of six electromyography acquisition setups on hand movement classification tasks
    Stefano Pizzolato, Luca Tagliapietra, Matteo Cognolato, Monica Reggiani, Henning Müller, Manfredo Atzori · 2017 · PLoS ONE
68. Forest aboveground biomass estimation using Landsat 8 and Sentinel-1A data with machine learning algorithms
    Zhenzhen Liu, Mingyang Li, Chao Li, Zhenzhen Liu · 2020 · Scientific Reports
69. Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
    Xinzhi Zhou, Haijia Wen, Yalan Zhang, Jiahui Xu, Wengang Zhang · 2021 · Geoscience Frontiers
70. A global map of local climate zones to support earth system modelling and urban-scale environmental science
    Matthias Demuzere, Jonas Kittner, Alberto Martilli, Gerald M. Mills, Christian Moede, Iain D. Stewart, Jasper van Vliet, Benjamin Bechtel · 2022 · Earth system science data
71. yaImpute : An R Package for k NN Imputation
    Nicholas L. Crookston, Andrew O. Finley · 2008 · Journal of Statistical Software
72. Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques
    Abid Ishaq, Saima Sadiq, Muhammad Umer, Saleem Ullah, Seyedali Mirjalili, Vaibhav Rupapara, Michele Nappi · 2021 · IEEE Access
73. A machine learning based credit card fraud detection using the GA algorithm for feature selection
    Emmanuel Ileberi, Yanxia Sun, Zenghui Wang · 2022 · Journal Of Big Data
74. Analyzing the Performance of Multilayer Neural Networks for Object Recognition
    Agrawal, Pulkit, Girshick, Ross, Malik, Jitendra · 2014 · Lecture Notes in Computer Science
75. Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects
    P. Richard Hahn, Jared S. Murray, Carlos M. Carvalho · 2017 · Bayesian Analysis
76. Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment
    Laura Judith Marcos-Zambrano, Kanita Karađuzović-Hadžiabdić, Tatjana Lončar-Turukalo, Piotr Przymus, Vladimir Trajkovik, Oliver Aasmets, Magali Berland, Aleksandra Gruca, Jasminka Hasić Telalović, Karel Hron et al. · 2021 · Frontiers in Microbiology
77. Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions
    Heslot, Nicolas, Akdemir, Deniz, Sorrells, Mark E., Jannink, Jean-Luc · 2014 · Theoretical and Applied Genetics
78. A comparative study of machine learning classifiers for modeling travel mode choice
    Hagenauer, Julian, Helbich, Marco · 2017 · Expert Systems with Applications
79. Spelling it out: Real-time ASL fingerspelling recognition
    Nicolas Pugeault, Richard Bowden · 2011 · IEEE International Conference on Computer Vision Workshops
80. Internet of Things (IoT) Security Intelligence: A Comprehensive Overview, Machine Learning Solutions and Research Directions
    Iqbal Hasan Sarker, Asif Irshad Khan, Yoosef B. Abushark, Fawaz Jaber Alsolami · 2022 · Mobile Networks and Applications
81. Comparison of Logistic Regression and Random Forests techniques for shallow landslide susceptibility assessment in Giampilieri (NE Sicily, Italy)
    Alessandro Trigila, Carla Iadanza, Carlo Esposito, Gabriele Scarascia Mugnozza · 2015 · Geomorphology
82. Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index
    Levin, Scott, Toerper, Matthew, Hamrock, Eric, Hinson, Jeremiah S., Barnes, Sean, Gardner, Heather, Dugas, Andrea, Linton, Bob, Kirsch, Tom, Kelen, Gabor · 2018 · Annals of Emergency Medicine
83. Constrained parametric min-cuts for automatic object segmentation
    João Carreira, Cristian Sminchisescu · 2010 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
84. PRoNTo: Pattern Recognition for Neuroimaging Toolbox
    Jessica Schrouff, Maria João Rosa, Jane Maryam Rondina, André F. Marquand, Carlton Chu, John Ashburner, Christophe L. M. Phillips, Jonas Richiardi, Janaı́na Mourão-Miranda · 2013 · Neuroinformatics
85. Algorithm runtime prediction: Methods & evaluation
    Frank Hutter, Lin Xu, Holger H. Hoos, Kevin Leyton‐Brown · 2013 · Artificial Intelligence
86. Satellite-based soybean yield forecast: Integrating machine learning and weather data for improving crop yield prediction in southern Brazil
    Raí Augusto Schwalbert, Telmo Jorge Carneiro Amado, Geomar Mateus Corassa, Luan Pierre Pott, P. V. Vara Prasad, Ignacio Antonio Ciampitti · 2020 · Agricultural and Forest Meteorology
87. Critical Assessment of QSAR Models of Environmental Toxicity against Tetrahymena pyriformis: Focusing on Applicability Domain and Overfitting by Variable Selection
    Igor V. Tetko, Iurii Sushko, Anil Kumar Pandey, Hao Zhu, Alexander Tropsha, Ester Papa, Tomas Öberg, Roberto Todeschini, Denis Fourches, Alexandre A. Varnek · 2008 · Journal of Chemical Information and Modeling
88. Digital mapping of soil organic matter stocks using Random Forest modeling in a semi-arid steppe ecosystem
    Martin Wiesmeier, Frauke Barthold, Benjamin Blank, Ingrid Kögel‐Knabner · 2010 · Plant and Soil
89. A spatio-temporal active-fire clustering approach for global burned area mapping at 250 m from MODIS data
    Joshua Lizundia-Loiola, Gonzalo Otón, Rubén Ramo, Emilio Chuvieco · 2019 · Remote Sensing of Environment
90. A Systematic Prediction of Multiple Drug-Target Interactions from Chemical, Genomic, and Pharmacological Data
    Hua Yu, Mantang Chen, Xue Jun Xu, Yan Li, Huihui Zhao, Yupeng Fang, Xiuxiu Li, Wei Zhou, Wei Wang, Yonghua Wang · 2012 · PLoS ONE
91. Correlation feature selection based improved-Binary Particle Swarm Optimization for gene selection and cancer classification
    Indu Jain, Vinod Kumar Jain, Renu Jain · 2017 · Applied Soft Computing
92. DeepDefense: Identifying DDoS Attack via Deep Learning
    Xiaoyong Yuan, Chuanhuang Li, Xiaolin Li · 2017 · IEEE International Conference on Smart Computing
93. Estimate of winter-wheat above-ground biomass based on UAV ultrahigh-ground-resolution image textures and vegetation indices
    Jibo Yue, Guijun Yang, Qingjiu Tian, Haikuan Feng, Kaijian Xu, Chengquan Zhou · 2019 · ISPRS Journal of Photogrammetry and Remote Sensing
94. Time-Series Classification with COTE: The Collective of Transformation-Based Ensembles
    Anthony J. Bagnall, Jason Lines, Jon Hills, Aaron George Bostrom · 2015 · IEEE Transactions on Knowledge and Data Engineering
95. AppScanner: Automatic Fingerprinting of Smartphone Apps from Encrypted Network Traffic
    Vincent F. Taylor, Riccardo Spolaor, Mauro Conti, Ivan Martinović · 2016 · IEEE European Symposium on Security and Privacy
96. A pan-cancer mycobiome analysis reveals fungal involvement in gastrointestinal and lung tumors
    Anders B. Dohlman, Jared Klug, Marissa Mesko, Iris Hanxing Gao, Steven M. Lipkin, Xiling Shen, Iliyan Dimitrov Iliev · 2022 · Cell
97. Arming the public with artificial intelligence to counter social bots
    Yang, Kai‐Cheng, Varol, Onur, Davis, Clayton A., Ferrara, Emilio, Flammini, Alessandro, Menczer, Filippo · 2019 · Human Behavior and Emerging Technologies
98. A first map of tropical Africa’s above-ground biomass derived from satellite imagery
    Alessandro Baccini, N. Laporte, S. J. Goetz, Meiou Sun, Haili Dong · 2008 · Environmental Research Letters
99. Gut microbial diversity in women with polycystic ovary syndrome correlates with hyperandrogenism
    Torres, Pedro J, Siakowska, Martyna, Banaszewska, Beata, Pawelczyk, Leszek, Duleba, Antoni J, Kelley, Scott T, Thackray, Varykina G · 2018 · The Journal of Clinical Endocrinology & Metabolism
100. A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions
     Wallace, R. John, Sasson, Goor, Garnsworthy, Philip C., Tapio, Ilma, Gregson, Emma, Bani, Paolo, Huhtanen, Pekka, Bayat, Ali R., Strozzi, Francesco, Biscarini, Filippo et al. · 2019 · Science Advances