Projects: pypi: scikit-learn
https://packages.ecosyste.ms/registries/pypi.org/packages/scikit-learn
A set of python modules for machine learning and data mining
72 versions
Latest release: about 3 years ago
5,918 dependent packages
43,777,417 downloads last month
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a.joly@ulg.ac.be
vanderplas@astro.washington.edu
bh00038@cvplws63.eps.surrey.ac.uk
ha258@cornell.edu
satra@mit.edu
zl2480@columbia.edu
pinto@alum.mit.edu
jz4721@nyu.edu
matteo.visconti.gr@dartmouth.edu
vighneshbirodkar@nyu.edu
robert.l.marchman@dartmouth.edu
rs2715@stern.nyu.edu
claire.savard@colorado.edu
aaaagrawal@iitb.ac.in
ihaque@cs.stanford.edu
rspeer@mit.edu
mluessi@nmr.mgh.harvard.edu
amitibo@tx.technion.ac.il
ericchang2017@u.northwestern.edu
jkarno@seas.upenn.edu
minghui.liu@trincoll.edu
m.lyra@sussex.ac.uk
andrew.knyazev@ucdenver.edu
lamb@cs.stanford.edu
camilo@neurostat.mit.edu
martino.sorbaro@ed.ac.uk
t.sheerman-chase@surrey.ac.uk
cgohlke@uci.edu
batulaa@drexel.edu
kcarnold@alum.mit.edu
apw@seas.harvard.edu
abie@alum.mit.edu
rossbar@berkeley.edu
alceballosa@unal.edu.co
fhoang7@berkeley.edu
hechen@seas.upenn.edu
stefan@sun.ac.za
deepyaman.datta@utexas.edu
rebekah.kim@columbia.edu
shubham.bhardwaj2015@vit.ac.in
slama@berkeley.edu
nisingh@wharton.upenn.edu
kanikas3@vt.edu
jdlabal@stanford.edu
kjells@uw.edu
markus.loning.17@ucl.ac.uk
k_nzw@klis.tsukuba.ac.jp
dkirkby@uci.edu
balawson@bu.edu
c.brummitt@columbia.edu
choo8@illinois.edu
giorgio.patrini@anu.edu.au
shangwuy@andrew.cmu.edu
rafael.possas@sydney.edu.au
olsonran@msu.edu
brian.mcfee@nyu.edu
naj273@nyu.edu
dgrusak@trinity.edu
emd222@cornell.edu
voth0@sewanee.edu
trishnendu.dd2014@cs.iiests.ac.in
apeng@berkeley.edu
boucher@cs.umass.edu
lunt@ctbp.ucsd.edu
bakhbari@mgh.harvard.edu
piraka@brandeis.edu
neal.lathia@cl.cam.ac.uk
razhoshia@post.bgu.ac.il
michal.romaniuk06@ic.ac.uk
m.batchkarov@sussex.ac.uk
lemin@cs.colostate.edu
rudvlf0413@korea.ac.kr
vredev16@msu.edu
raschkas@msu.edu
ali.baharev@univie.ac.at
a.krasoulis@sms.ed.ac.uk
arokem@berkeley.edu
gabrielvr@al.insper.edu.br
eric.sanchez1234@email.bakersfieldcollege.edu
fcchou@stanford.edu
rofuyu@cs.utexas.edu
glemaitre@visor.udg.edu
naoyaiijima@hiroshima-u.ac.jp
ayushgup@iitk.ac.in
joel@vlan-2666-10-17-16-173.staff.wireless.sydney.edu.au
jam7w2@mail.missouri.edu
j.hale09@imperial.ac.uk
tw991@nyu.edu
patel_zeel@iitgn.ac.in
vincent.lostanlen@nyu.edu
stvjc@channing.harvard.edu
ritchieng@u.nus.edu
bansalsi@usc.edu
rbarnes@umn.edu
rrohan@cs.cmu.edu
liutong.zhou@columbia.edu
mdh386@nyu.edu
mlf419@nyu.edu
shreyave@usc.edu
jin.siy@northeastern.edu
samuel_ainsworth@brown.edu
cwijes1@lsu.edu
wadawson@ucdavis.edu
xinyuliu@umich.edu
rz258@cornell.edu
daniel.mallia21@myhunter.cuny.edu
argriffi@ncsu.edu
filipj@umich.edu
kms15@case.edu
sam.dixon@berkeley.edu
khong008@e.ntu.edu.sg
jnelso11@gmu.edu
jclawton@umich.edu
jaehyunahn@sogang.ac.kr
ijpulidos@unal.edu.co
gstupp@scripps.edu
justhube@umich.edu
noamkeidar@campus.technion.ac.il
nityamd@nyu.edu
css459@nyu.edu
alyee@ucsd.edu
andersk@mit.edu
dhanus@mit.edu
coreylevinson@uchicago.edu
cailean.carter@quadram.ac.uk
bral4884@colorado.edu
dschult@colgate.edu
dpwe@ee.columbia.edu
dylan.cashman@tufts.edu
pawelsendyk@berkeley.edu
qzhang90@gatech.edu
mhaberla@calpoly.edu
saketk@student.unimelb.edu.au
eunjikim@dm.snu.ac.kr
erinrhof@uw.edu
ksivaman@purdue.edu
garmstrong@ucsd.edu
konstantin.shmelkov@polytechnique.edu
e175774@ie.u-ryukyu.ac.jp
hermidal@cs.umd.edu
jbearer@hmc.edu
jmarin@csail.mit.edu
Repository Activity:
Repository Owner:
scikit-learn (organization)
Repositories related to the scikit-learn Python machine learning library. Academic
Repositories related to the scikit-learn Python machine learning library. Academic
README Analysis:
Science Score: 100/100
Starting Score: 100 points
Bonuses:
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+2840
Educational commit emails
142 contributors with educational email addresses -
+20
Academic repository owner
Repository owned by academic institution -
+15
Institutional repository owner
Repository owned by research institution -
+6
Science terms in README
3 scientific terms found in README
Penalties:
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PyPI ecosystem
General-purpose ecosystem
Very Likely Science (100)
Papers Mentioning scikit-learn 2,431
10.3389/fnbot.2021.704226
A Novel sEMG-Based Gait Phase-Kinematics-Coupled Predictor and Its Interaction With ExoskeletonsCited by: 3
Author(s): Baichun Wei, Zhen Ding, Chunzhi Yi, Hao Guo, Zhipeng Wang, Jianfei Zhu, Feng Jiang
Software Mentions: 1
Published: over 5 years ago
10.3389/fnbot.2021.659311
Toward More Robust Hand Gesture Recognition on EIT DataCited by: 5
Author(s): David P. Leins, Christian Gibas, Rainer Brück, Robert Haschke
Software Mentions: 1
Published: about 5 years ago
10.3389/fnins.2021.697870
Autism Spectrum Disorder Studies Using fMRI Data and Machine Learning: A ReviewCited by: 19
Author(s): Meijie Liu, Baojuan Li, Dewen Hu
Software Mentions: 1
Published: about 5 years ago
10.3389/fnins.2021.611962
Adaptive Filtering for Improved EEG-Based Mental Workload Assessment of Ambulant UsersCited by: 19
Author(s): Olivier Rosanne, Isabela Albuquerque, Raymundo Cassani, Jean‐François Gagnon, Sébastien Tremblay, Tiago H. Falk
Software Mentions: 1
Published: over 5 years ago
10.3389/fnins.2021.669595
Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS DatabasesCited by: 13
Author(s): Jianfeng Wu, Qunxi Dong, Jie Gui, Jie Zhang, Yi Su, Kewei Chen, Paul M. Thompson, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Yalin Wang
Software Mentions: 1
Published: over 5 years ago
10.3389/fnins.2019.01023
Investigating the Effects of Mechanical Stimulation on Retinal Ganglion Cell Spontaneous Spiking ActivityCited by: 10
Author(s): Marica Marrese, Davide Lonardoni, Fabio Boi, Hedde van Hoorn, Alessandro Maccione, Stefano Zordan, Davide Iannuzzi, Luca Berdondini
Software Mentions: 1
Published: about 7 years ago
10.3389/fnins.2015.00328
Identification of resilient individuals and those at risk for performance deficits under stressCited by: 17
Author(s): Brent Winslow, Meredith Carroll, Jonathan W. Martin, Glenn Surpris, George L. Chadderdon
Software Mentions: 1
Published: about 11 years ago
10.3389/fnins.2014.00167
Which fMRI clustering gives good brain parcellations?Cited by: 248
Author(s): Bertrand Thirion, Gaël Varoquaux, Elvis Dohmatob, Jean‐Baptiste Poline
Software Mentions: 1
Published: over 12 years ago
10.3389/fnins.2020.00593
EEG Channel-Selection Method for Epileptic-Seizure Classification Based on Multi-Objective OptimizationCited by: 45
Author(s): Luis Alfredo Moctezuma, Marta Molinas
Software Mentions: 1
Published: over 6 years ago
10.3389/fnins.2021.661504
Multiparametric MRI for Characterization of the Basal Ganglia and the MidbrainCited by: 4
Author(s): Till Schneider, Jackie Ma, Patrick Wagner, Nicolas G.R. Behl, Armin M. Nagel, Mark E. Ladd, Sabine Heiland, Martin Bendszus
Software Mentions: 1
Published: over 5 years ago
10.3389/fnins.2021.664490
Imaging Time Series of Eye Tracking Data to Classify Attentional StatesCited by: 7
Author(s): Lisa-Marie Vortmann, Jannes Knychalla, Sonja Annerer‐Walcher, Mathias Benedek, Felix Putze
Software Mentions: 1
Published: over 5 years ago
10.3389/fnins.2018.00038
Multivariate Classification of Major Depressive Disorder Using the Effective Connectivity and Functional ConnectivityCited by: 45
Author(s): Xiang-Fei Geng, Junhai Xu, Baolin Liu, Yonggang Shi
Software Mentions: 1
Published: over 8 years ago
10.3389/fnins.2020.588357
Hyperscanning EEG and Classification Based on Riemannian Geometry for Festive and Violent Mental State DiscriminationCited by: 5
Author(s): Cédric Simar, Ana Maria Cebolla, Gaëlle Chartier, Mathieu Petieau, Gianluca Bontempi, Alain Berthoz, Guy Chéron
Software Mentions: 1
Published: almost 6 years ago
10.3389/fnins.2020.605697
Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI FeaturesCited by: 8
Author(s): Bartosz Bohaterewicz, Anna Maria Sobczak, Igor T. Podolak, Bartosz Wójcik, Dagmara Mętel, Adrian Andrzej Chrobak, Magdalena Fa Frowicz, Marcin Siwek, Dominika Dudek, Tadeusz Marek
Software Mentions: 1
Published: almost 6 years ago
10.3389/fnins.2019.00891
Effect of User Practice on Prosthetic Finger Control With an Intuitive Myoelectric DecoderCited by: 32
Author(s): Agamemnon Krasoulis, Sethu Vijayakumar, Kianoush Nazarpour
Software Mentions: 1
Published: about 7 years ago
10.3389/fnins.2018.00967
Longitudinal Connectomes as a Candidate Progression Marker for Prodromal Parkinson’s DiseaseCited by: 13
Author(s): Óscar Peña‐Nogales, Timothy M. Ellmore, Rodrigo de Luis‐García, Jessika Suescun, Mya C. Schiess, Luca Giancardo
Software Mentions: 1
Published: almost 8 years ago
10.3389/fnins.2020.558434
Investigation on the Alteration of Brain Functional Network and Its Role in the Identification of Mild Cognitive ImpairmentCited by: 10
Author(s): Lulu Zhang, Huangjing Ni, Yu Zhang, Jun Wang, Qin Jiang, Fengzhen Hou, Albert C. Yang, Alzheimer’s Disease Neuroimaging Initiative
Software Mentions: 1
Published: about 6 years ago
10.3389/fonc.2020.585767
Multiregional-Based Magnetic Resonance Imaging Radiomics Combined With Clinical Data Improves Efficacy in Predicting Lymph Node Metastasis of Rectal CancerCited by: 23
Author(s): Xiangchun Liu, Qi Yang, Chunyu Zhang, Jianqing Sun, Kan He, Yunming Xie, Yiying Zhang, Yu Fu, Huimao Zhang
Software Mentions: 1
Published: over 5 years ago
10.3389/fonc.2020.607923
Deep Neural Networks Outperform the CAPRA Score in Predicting Biochemical Recurrence After ProstatectomyCited by: 6
Author(s): P. Sargos, Nicolas Leduc, Nicolas Giraud, Giorgio Gandaglia, M. Roumiguié, Guillaume Ploussard, François Rozet, M. Soulié, Romain Mathiéu, P. Mongiat Artus, Tamim Niazi, Vincent Vinh-Hung, Jean-Baptiste Beauval
Software Mentions: 1
Published: over 5 years ago
10.3389/fonc.2020.01676
Machine Learning-Based Radiomics Predicting Tumor Grades and Expression of Multiple Pathologic Biomarkers in GliomasCited by: 18
Author(s): Min Gao, Siying Huang, Xuequn Pan, Xiangyun Liao, Ru Yang, Jun Liu
Software Mentions: 1
Published: about 6 years ago
10.3389/fonc.2021.642945
Prediction of Target-Drug Therapy by Identifying Gene Mutations in Lung Cancer With Histopathological Stained Image and Deep Learning TechniquesCited by: 6
Author(s): Kaimei Huang, Zhiyi Mo, Wen Zhu, Bo Liao, Yachao Yang, Fang‐Xiang Wu
Software Mentions: 1
Published: over 5 years ago
10.3389/fonc.2020.00937
Radiomics Features Predict CIC Mutation Status in Lower Grade GliomaCited by: 15
Author(s): Luyuan Zhang, Felipe Giuste, Juan C. Vizcarra, Xuejun Li, David Gutman
Software Mentions: 1
Published: over 6 years ago
10.3389/fonc.2020.01186
CT-Based Deep Learning Model for Invasiveness Classification and Micropapillary Pattern Prediction Within Lung AdenocarcinomaCited by: 15
Author(s): Huang Ding, Wenjie Xia, Lei Zhang, Qixing Mao, Bowen Cao, Yihang Zhao, Lin Xu, Feng Jiang, Gaochao Dong
Software Mentions: 1
Published: over 6 years ago
10.3389/fonc.2020.00752
Machine-Learning Classifiers in Discrimination of Lesions Located in the Anterior Skull BaseCited by: 22
Author(s): Yang Zhang, Lan Shang, Chaoyue Chen, Xuelei Ma, Xuejin Ou, Jian Wang, Fan Xia, Jianguo Xu
Software Mentions: 1
Published: over 6 years ago
10.3389/fonc.2021.709137
Prediction of EGFR Mutation Status Based on 18F-FDG PET/CT Imaging Using Deep Learning-Based Model in Lung AdenocarcinomaCited by: 8
Author(s): Guang Yin, Ziyang Wang, Yan Song, Xiaofeng Li, Yiwen Chen, Lihong Zhu, Qian Su, Diansheng Dong, Wengui Xu
Software Mentions: 1
Published: over 5 years ago
10.3389/fonc.2020.608598
Machine Learning for Histologic Subtype Classification of Non-Small Cell Lung Cancer: A Retrospective Multicenter Radiomics StudyCited by: 16
Author(s): Fang Yang, Wei Chen, Haifeng Wei, Xianru Zhang, Shuanghu Yuan, Qiao Xu, Yen‐Wei Chen
Software Mentions: 1
Published: almost 6 years ago
10.3389/fonc.2019.01338
The Diagnostic Value of Radiomics-Based Machine Learning in Predicting the Grade of Meningiomas Using Conventional Magnetic Resonance Imaging: A Preliminary StudyCited by: 47
Author(s): Chaoyue Chen, Xinyi Guo, Jian Wang, Wen Guo, Xuelei Ma, Jianguo Xu
Software Mentions: 1
Published: almost 7 years ago
10.3389/fonc.2021.639062
Differentiation of Glioma Mimicking Encephalitis and Encephalitis Using Multiparametric MR-Based Deep LearningCited by: 9
Author(s): Wenli Wu, Jiewen Li, Junyong Ye, Qi Wang, Wentao Zhang, Shengsheng Xu
Software Mentions: 1
Published: over 5 years ago
10.3389/fonc.2021.638262
Development of a Machine Learning Classifier Based on Radiomic Features Extracted From Post-Contrast 3D T1-Weighted MR Images to Distinguish Glioblastoma From Solitary Brain MetastasisCited by: 15
Author(s): Alix de Causans, Alexandre Carré, Alexandre Roux, Arnault Tauziède‐Espariat, Samy Ammari, Edouard Dezamis, Frédéric Dhermain, Sylvain Reuzé, Éric Deutsch, Catherine Oppenheim, Pascale Varlet, Johan Pallud, Myriam Edjlali, Charlotte Robert
Software Mentions: 1
Published: over 5 years ago
10.3389/fped.2020.570834
Comparison of Machine Learning Models for Prediction of Initial Intravenous Immunoglobulin Resistance in Children With Kawasaki DiseaseCited by: 4
Author(s): Yasutaka Kuniyoshi, Haruka Tokutake, Natsuki Takahashi, Azusa Kamura, Sumie Yasuda, M. Tashiro
Software Mentions: 1
Published: almost 6 years ago
10.3389/fphar.2017.00816
Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct FeaturesCited by: 34
Author(s): Jaimit Parikh, Viatcheslav Gurev, John Jeremy Rice
Software Mentions: 1
Published: almost 9 years ago
10.3389/fphar.2018.01036
Identification of Antioxidant Proteins With Deep Learning From Sequence InformationCited by: 12
Author(s): Lifen Shao, Hui Gao, Zhen Liu, Juan Feng, Lixia Tang, Hao Lin
Software Mentions: 1
Published: about 8 years ago
10.3389/fphar.2019.01570
Chinese Herbal Medicine (MaZiRenWan) Improves Bowel Movement in Functional Constipation Through Down-Regulating OleamideCited by: 9
Author(s): Tao Huang, Ling Zhao, Chengyuan Lin, Lin Lü, Ziwan Ning, Dong-Dong Hu, Linda L. D. Zhong, Zhijun Yang, Zhaoxiang Bian
Software Mentions: 1
Published: almost 7 years ago
10.3389/fphar.2020.00069
Predicting or Pretending: Artificial Intelligence for Protein-Ligand Interactions Lack of Sufficiently Large and Unbiased DatasetsCited by: 71
Author(s): Jincai Yang, Cheng Shen, Niu Huang
Software Mentions: 1
Published: over 6 years ago
10.3389/fphar.2019.00913
Identification of Novel Antibacterials Using Machine Learning TechniquesCited by: 27
Author(s): Yan A. Ivanenkov, Alex Zhavoronkov, R. S. Yamidanov, Ilya А. Osterman, Петр В. Сергиев, Vladimir Aladinskiy, Anastasia V. Aladinskaya, Victor A Terentiev, Mark S. Veselov, Andrey A. Ayginin, В. Г. Карцев, Dmitry A. Skvortsov, А. В. Чемерис, Alexey Kh Baimiev, Alina A. Sofronova, Alexander S. Malyshev, Gleb I. Filkov, Dmitry S. Bezrukov, Bogdan Zagribelnyy, Evgeny Putin, Maria M Puchinina, Olga А. Dontsova
Software Mentions: 1
Published: about 7 years ago
10.3389/fphar.2020.00112
EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality PredictionCited by: 13
Author(s): Fangping Wan, Shuya Li, Tingzhong Tian, Yipin Lei, Dan Zhao, Jianyang Zeng
Software Mentions: 1
Published: over 6 years ago
10.3389/fphys.2020.572874
In silico Comparison of Left Atrial Ablation Techniques That Target the Anatomical, Structural, and Electrical Substrates of Atrial FibrillationCited by: 34
Author(s): Caroline Roney, Marianne Beach, Arihant Mehta, Iain Sim, Cesare Corrado, Rokas Bendikas, José Alonso Solís-Lemus, Orod Razeghi, John Whitaker, Louisa O’Neill, Gernot Plank, Edward J. Vigmond, Steven E. Williams, Mark O’Neill, Steven Niederer
Software Mentions: 1
Published: about 6 years ago
10.3389/fphys.2021.674106
Toward Patient-Specific Prediction of Ablation Strategies for Atrial Fibrillation Using Deep LearningCited by: 10
Author(s): Marica Muffoletto, Ahmed Qureshi, Aya Mutaz Zeidan, Laila Muizniece, Xiao Fu, Jichao Zhao, Aditi Roy, Paul A. Bates, Oleg Aslanidi
Software Mentions: 1
Published: over 5 years ago
10.3389/fphys.2021.704122
Deep Learning Classification of Unipolar Electrograms in Human Atrial Fibrillation: Application in Focal Source MappingCited by: 7
Author(s): S. Matthew Liao, Don Ragot, Sachin Nayyar, Adrian Suszko, Zhaolei Zhang, Bo Wang, Vijay S. Chauhan
Software Mentions: 1
Published: over 5 years ago
10.3389/fpls.2018.00603
Phenotyping of Arabidopsis Drought Stress Response Using Kinetic Chlorophyll Fluorescence and Multicolor Fluorescence ImagingCited by: 81
Author(s): Jieni Yao, Dawei Sun, Haiyan Cen, Haixia Xu, Haiyong Weng, Fang Yuan, Yong He
Software Mentions: 1
Published: over 8 years ago
10.3389/fpls.2016.01936
A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in ArabidopsisCited by: 38
Author(s): Ying Ni, Delasa Aghamirzaie, Haitham Elmarakeby, Eva Collakova, Li Song, Ruth Grene, Lenwood S. Heath
Software Mentions: 1
Published: almost 10 years ago
10.3389/fpls.2018.01734
A Pipeline for Classifying Deleterious Coding Mutations in Agricultural PlantsCited by: 7
Author(s): Maxim S. Kovalev, Anna A. Igolkina, Maria Samsonova, Sergey V. Nuzhdin
Software Mentions: 1
Published: almost 8 years ago
10.3389/fpls.2020.590529
Machine Learning Techniques for Soybean Charcoal Rot Disease PredictionCited by: 20
Author(s): Elham Khalili, Samaneh Kouchaki, Shahin Ramazi, Faezeh Ghanati
Software Mentions: 1
Published: almost 6 years ago
10.3389/fpls.2016.01451
Better Than Nothing? Limitations of the Prediction Tool SecretomeP in the Search for Leaderless Secretory Proteins (LSPs) in PlantsCited by: 23
Author(s): Andrew Lonsdale, Melissa J. Davis, Monika S. Doblin, Antony Bacic
Software Mentions: 1
Published: about 10 years ago
10.3389/fpls.2019.00227
Leaf-Movement-Based Growth Prediction Model Using Optical Flow Analysis and Machine Learning in Plant FactoryCited by: 25
Author(s): Shogo Nagano, Shogo Moriyuki, Kazumasa Wakamori, Hiroshi Mineno, Hirokazu Fukuda
Software Mentions: 1
Published: over 7 years ago
10.3389/fpls.2019.01281
Mapping Aboveground Biomass of Four Typical Vegetation Types in the Poyang Lake Wetlands Based on Random Forest Modelling and Landsat ImagesCited by: 18
Author(s): Rongrong Wan, Peng Wang, Xiaolong Wang, Xing Yao, Xue Dai
Software Mentions: 1
Published: about 7 years ago
10.3389/fpls.2018.01102
On-The-Go Hyperspectral Imaging Under Field Conditions and Machine Learning for the Classification of Grapevine VarietiesCited by: 46
Author(s): Salvador Gutiérrez, Juan Fernández‐Novales, María P. Diago, Javier Tardáguila
Software Mentions: 1
Published: over 8 years ago
10.3389/fpls.2020.575810
Wheat Kernel Variety Identification Based on a Large Near-Infrared Spectral Dataset and a Novel Deep Learning-Based Feature Selection MethodCited by: 28
Author(s): Lei Zhou, Chu Zhang, Mohamed Farag Taha, Xinhua Wei, Yong He, Zhengjun Qiu, Yufei Liu
Software Mentions: 1
Published: almost 6 years ago
10.3389/fpls.2019.00155
Deep Learning-Based Segmentation and Quantification of Cucumber Powdery Mildew Using Convolutional Neural NetworkCited by: 125
Author(s): Ke Lin, Liang Gong, Yongfeng Huang, Chengliang Liu, Junsong Pan
Software Mentions: 1
Published: over 7 years ago
10.3389/fpsyt.2020.531801
Decomposed Temporal Complexity Analysis of Neural Oscillations and Machine Learning Applied to Alzheimer’s Disease DiagnosisCited by: 3
Author(s): Naoki Furutani, Yuta Nariya, Tetsuya Takahashi, Sarah Noto, Albert C. Yang, Tetsu Hirosawa, Masafumi Kameya, Yoshio Minabe, Mitsuru Kikuchi
Software Mentions: 1
Published: about 6 years ago
10.3389/fpsyt.2021.598518
Predicting Brain Age at Slice Level: Convolutional Neural Networks and Consequences for InterpretabilityCited by: 9
Author(s): Pedro Ballester, Laura Tomaz da Silva, Matheus Marcon, Nathália Bianchini Esper, Benício N. Frey, Augusto Buchweitz, Felipe Meneguzzi
Software Mentions: 1
Published: over 5 years ago
10.3389/fpsyt.2021.728278
What Factors Are Most Closely Associated With Mood Disorders in Adolescents During the COVID-19 Pandemic? A Cross-Sectional Study Based on 1,771 Adolescents in Shandong Province, ChinaCited by: 38
Author(s): Ziyuan Ren, Yaodong Xin, Zhong Lin Wang, Dexiang Liu, Roger Ho, Cyrus S.H. Ho
Software Mentions: 1
Published: about 5 years ago
10.3389/fpsyt.2020.00189
Proteomic Profiling as a Diagnostic Biomarker for Discriminating Between Bipolar and Unipolar DepressionCited by: 9
Author(s): Sarah Kittel‐Schneider, Tim Hahn, F. Haenisch, Rhiannon V. McNeill, Andreas Reif, Sabine Bahn
Software Mentions: 1
Published: over 6 years ago
10.3389/fpsyt.2020.00144
Classification of Social Anxiety Disorder With Support Vector Machine Analysis Using Neural Correlates of Social Signals of ThreatCited by: 13
Author(s): Mengqi Xing, Jacklynn M. Fitzgerald, Heide Klumpp
Software Mentions: 1
Published: over 6 years ago
10.3389/fpsyt.2020.593336
Ensemble Learning of Convolutional Neural Network, Support Vector Machine, and Best Linear Unbiased Predictor for Brain Age Prediction: ARAMIS Contribution to the Predictive Analytics Competition 2019 ChallengeCited by: 18
Author(s): Baptiste Couvy‐Duchesne, Johann Faouzi, Benoît Martin, Elina Thibeau–Sutre, Adam Wild, Manon Ansart, Stanley Durrleman, Didier Dormont, Ninon Burgos, Olivier Colliot
Software Mentions: 1
Published: almost 6 years ago
10.3389/fpsyt.2021.655292
Deep Neural Network to Differentiate Brain Activity Between Patients With First-Episode Schizophrenia and Healthy Individuals: A Multi-Channel Near Infrared Spectroscopy StudyCited by: 12
Author(s): Po-Han Chou, Yun Han Yao, Rui Zheng, Yi Long Liou, Tsung Te Liu, Hsien Yuan Lane, Albert C. Yang, Shao-Cheng Wang
Software Mentions: 1
Published: over 5 years ago
10.3389/fpsyg.2021.647956
Securing Your Relationship: Quality of Intimate Relationships During the COVID-19 Pandemic Can Be Predicted by Attachment StyleCited by: 18
Author(s): Stephanie J. Eder, Andrew A. Nicholson, Michał Stefańczyk, Michał Pieniak, Judit Martínez-Molina, Ondra Pešout, Jakub Binter, Patrick Smela, Frank Scharnowski, David Steyrl
Software Mentions: 1
Published: over 5 years ago
10.3389/fpsyg.2021.604522
A Recurrent Neural Network for Attenuating Non-cognitive Components of Pupil DynamicsCited by: 1
Author(s): Sharath Koorathota, Kaveri A. Thakoor, Linbi Hong, Yaoli Mao, Patrick Adelman, Paul Sajda
Software Mentions: 1
Published: almost 6 years ago
10.3389/fpsyg.2020.551548
Fatigue-Related and Timescale-Dependent Changes in Individual Movement Patterns Identified Using Support Vector MachineCited by: 13
Author(s): Johannes Burdack, Fabian Horst, Daniel Aragonés, Alexander Eekhoff, Wolfgang I. Schöllhorn
Software Mentions: 1
Published: about 6 years ago
10.3389/fpsyg.2018.01545
Good Things for Those Who Wait: Predictive Modeling Highlights Importance of Delay Discounting for Income AttainmentCited by: 13
Author(s): William Heyward Hampton, Nima Asadi, Ingrid R. Olson
Software Mentions: 1
Published: about 8 years ago
10.3389/fpubh.2021.630640
Work Habit-Related Sleep Debt; Insights From Factor Identification Analysis of Actigraphy DataCited by: 7
Author(s): Yuki Goto, Koichi Fujiwara, Yukiyoshi Sumi, Masahiro Matsuo, Manabu Kano, Hiroshi Kadotani
Software Mentions: 1
Published: over 5 years ago
10.3389/frobt.2018.00035
Tracking All Members of a Honey Bee Colony Over Their Lifetime Using Learned Models of CorrespondenceCited by: 35
Author(s): Franziska Boenisch, Benjamin Rosemann, Benjamin Wild, David Dormagen, Fernando Wario, Tim Landgraf
Software Mentions: 1
Published: over 8 years ago
10.3389/frobt.2019.00077
Incremental and Parallel Machine Learning Algorithms With Automated Learning Rate AdjustmentsCited by: 2
Author(s): Kazuhiro Hishinuma, Hideaki Iiduka
Software Mentions: 1
Published: about 7 years ago
10.3389/frobt.2018.00085
Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUsCited by: 5
Author(s): Naomi T. Fitter, Katherine J. Kuchenbecker
Software Mentions: 1
Published: over 8 years ago
10.3389/frobt.2021.672315
Optical-Tactile Sensor for Lump Detection Using Pneumatic ControlCited by: 6
Author(s): Jonathan Bewley, George P. Jenkinson, Antonia Tzemanaki
Software Mentions: 1
Published: over 5 years ago
10.3389/frobt.2019.00124
Tactile Signatures and Hand Motion Intent Recognition for Wearable Assistive DevicesCited by: 7
Author(s): Thekla Stefanou, Greg Chance, Tareq Assaf, Sanja Dogramadzi
Software Mentions: 1
Published: almost 7 years ago
10.3389/frobt.2021.729832
Automatic Detection of Gaze and Body Orientation in Elementary School ClassroomsCited by: 3
Author(s): Roberto Araya, Jorge Sossa-Rivera
Software Mentions: 1
Published: about 5 years ago
10.3389/frobt.2021.696587
Aiding Grasp Synthesis for Novel Objects Using Heuristic-Based and Data-Driven Active Vision MethodsCited by: 1
Author(s): Sabhari Natarajan, Galen Brown, Berk Çallı
Software Mentions: 1
Published: over 5 years ago
10.3389/frobt.2020.522141
A Framework for Sensorimotor Cross-Perception and Cross-Behavior Knowledge Transfer for Object CategorizationCited by: 5
Author(s): Gyan Tatiya, Ramtin Hosseini, Michael C. Hughes, Jivko Sinapov
Software Mentions: 1
Published: about 6 years ago
10.3389/frobt.2019.00092
Unsupervised Phoneme and Word Discovery From Multiple Speakers Using Double Articulation Analyzer and Neural Network With Parametric BiasCited by: 3
Author(s): Ryoichi Nakashima, Ryo Ozaki, Tadahiro Taniguchi
Software Mentions: 1
Published: about 7 years ago
10.3389/frobt.2020.00038
A Robust Screen-Free Brain-Computer Interface for Robotic Object SelectionCited by: 0
Author(s): Henrich Kolkhorst, Joseline Veit, Wolfram Burgard, Michael Tangermann
Software Mentions: 1
Published: over 6 years ago
10.3389/fvets.2021.639249
Three-Dimensional Live Imaging of Bovine Preimplantation Embryos: A New Method for IVF Embryo EvaluationCited by: 4
Author(s): Yasumitsu Masuda, Ryo Hasebe, Yasushi Kuromi, Masayoshi Kobayashi, Kanako Urataki, Mitsugu Hishinuma, Tetsuya Ohbayashi, Ryo Nishimura
Software Mentions: 1
Published: over 5 years ago
10.2144/fsoa-2019-0131
Integrating computational lead optimization diagnostics with analog design and candidate selectionCited by: 5
Author(s): Dimitar Yonchev, Jürgen Bajorath
Software Mentions: 1
Published: over 6 years ago
10.1534/g3.115.025882
Genome-Wide Analysis of the TORC1 and Osmotic Stress Signaling Network in<i>Saccharomyces cerevisiae</i>Cited by: 9
Author(s): Jeremy Worley, Arron Sullivan, Xiangxia Luo, Matt Kaplan, Andrew P. Capaldi
Software Mentions: 1
Published: almost 11 years ago
10.1534/g3.120.401122
QTG-Finder2: A Generalized Machine-Learning Algorithm for Prioritizing QTL Causal Genes in PlantsCited by: 6
Author(s): Fan Lin, Elena Lazarus, Seung Y. Rhee
Software Mentions: 1
Published: over 6 years ago
10.3390/genes10100812
Identification of Key Genes for the Precise Classification between Solenopsis invicta and S. geminata Facilitating the Quarantine ProcessCited by: 2
Author(s): Kil-Hyun Kim, Jisu Kim, Hyun-Ji Cho, Jong-Ho Lee, Tae-Hwan Jun, Yang-Jae Kang
Software Mentions: 1
Published: about 7 years ago
10.3390/genes10110836
Deregulated Adhesion Program in Palatal Keratinocytes of Orofacial Cleft PatientsCited by: 1
Author(s): Aysel Mammadova, Carine Carels, Jie Zhou, Christian Gilissen, Maria P. A. C. Helmich, Zhuan Bian, Huiqing Zhou, Johannes W. Von den Hoff
Software Mentions: 1
Published: about 7 years ago
10.3390/genes12040564
OTUs and ASVs Produce Comparable Taxonomic and Diversity from Shrimp Microbiota 16S Profiles Using Tailored Abundance FiltersCited by: 19
Author(s): Rodrigo García-López, Fernanda Cornejo‐Granados, Alonso A. López-Zavala, Andrés Cota-Huízar, Rogerio R. Sotelo‐Mundo, Bruno Gómez‐Gil, Adrián Ochoa-Leyva
Software Mentions: 1
Published: over 5 years ago
10.1534/genetics.120.303093
Machine Learning Techniques for Classifying the Mutagenic Origins of Point MutationsCited by: 7
Author(s): Yicheng Zhu, Cheng Soon Ong, Gavin A. Huttley
Software Mentions: 1
Published: over 6 years ago
10.1186/s13059-017-1217-z
Optimizing complex phenotypes through model-guided multiplex genome engineeringCited by: 22
Author(s): Gleb Kuznetsov, Daniel B. Goodman, Gabriel T. Filsinger, Matthieu Landon, Nadin Rohland, John Aach, Marc J. Lajoie, George M. Church
Software Mentions: 1
Published: over 9 years ago
10.1186/s13059-019-1784-2
A unified encyclopedia of human functional DNA elements through fully automated annotation of 164 human cell typesCited by: 37
Author(s): Maxwell W. Libbrecht, Oscar L. Rodriguez, Zhiping Weng, Jeffrey A. Bilmes, Michael M. Hoffman, William Stafford Noble
Software Mentions: 1
Published: about 7 years ago
10.1186/s13073-015-0189-4
Inferring pathway dysregulation in cancers from multiple types of omic dataCited by: 13
Author(s): Shelley M. MacNeil, W. Evan Johnson, Dean Y. Li, Stephen R. Piccolo, Andrea Bild
Software Mentions: 1
Published: over 11 years ago
10.1186/s13073-018-0571-0
Exploring the OncoGenomic Landscape of cancerCited by: 7
Author(s): Lídia Mateo, Oriol Guitart-Pla, Miquel Duran‐Frigola, Patrick Aloy
Software Mentions: 1
Published: over 8 years ago
10.1186/s13073-020-00775-w
CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variationsCited by: 26
Author(s): Shuang Li, K. Joeri van der Velde, Dick de Ridder, Aalt D. J. van Dijk, Dimitrios Soudis, Leslie R. Zwerwer, Patrick Deelen, Dennis Hendriksen, Bart Charbon, Mariëlle van Gijn, Kristin M. Abbott, Birgit Sikkema‐Raddatz, Cleo C. van Diemen, Wilhelmina S. Kerstjens‐Frederikse, Richard J. Sinke, Morris A. Swertz
Software Mentions: 1
Published: about 6 years ago
10.5808/GI.2019.17.3.e30
Deep learning for stage prediction in neuroblastoma using gene expression dataCited by: 5
Author(s): Aron Park, Seungyoon Nam
Software Mentions: 1
Published: about 7 years ago
10.1093/gigascience/gix115
CNVcaller: highly efficient and widely applicable software for detecting copy number variations in large populationsCited by: 71
Author(s): Xihong Wang, Zhuqing Zheng, Yi Cai, Ting Chen, Chao Li, Weiwei Fu, Yu Jiang
Software Mentions: 1
Published: almost 9 years ago
10.1007/s13755-020-00123-7
A hybrid AI approach for supporting clinical diagnosis of attention deficit hyperactivity disorder (ADHD) in adultsCited by: 32
Author(s): Ilias Tachmazidis, Tianhua Chen, Marios Adamou, Grigoris Antoniou
Software Mentions: 1
Published: almost 6 years ago
10.3390/healthcare9091107
The Feasibility of Using Machine Learning to Classify Calls to South African Emergency Dispatch Centres According to Prehospital Diagnosis, by Utilising Caller Descriptions of the IncidentCited by: 4
Author(s): T. Newall Anthony, Amit Kumar Mishra, Willem Stassen, Jarryd Son
Software Mentions: 1
Published: about 5 years ago
10.3390/healthcare6020055
Fecal Distribution Changes Using Colorectal Ultrasonography in Older People with Physical and Cognitive Impairment Living in Long-Term Care Facilities: A Longitudinal Observational StudyCited by: 11
Author(s): Shiho Tanaka, Koichi Yabunaka, Masaru Matsumoto, Nao Tamai, Hiroshi Noguchi, Mikako Yoshida, Gojiro Nakagami, Junko Sugama, Hiromi Sanada
Software Mentions: 1
Published: over 8 years ago
10.3390/healthcare9091148
Predicting Emotional Valence of People Living with the Human Immunodeficiency Virus Using Daily Voice Clips: A Preliminary StudyCited by: 1
Author(s): Ray F. Lin, Shu‐Hsing Cheng, Yung-Ping Liu, Cheng-Pin Chen, Yi-Jyun Wang, Shu-Ying Chang
Software Mentions: 1
Published: about 5 years ago
10.1109/access.2021.3093005
Fast and Scalable Private Genotype Imputation Using Machine Learning and Partially Homomorphic EncryptionCited by: 14
Author(s): Esha Sarkar, Eduardo Ottobelli Chielle, Gamze Gürsoy, Oleg Mazonka, Mark Gerstein, Michail Maniatakos
Software Mentions: 1
Published: almost 6 years ago
10.1109/JTEHM.2020.2982150
Convex Representations Using Deep Archetypal Analysis for Predicting GlaucomaCited by: 14
Author(s): Anshul Thakur, Michael H. Goldbaum, Siamak Yousefi
Software Mentions: 1
Published: almost 7 years ago
10.1098/rsos.192043
Decoding and encoding models reveal the role of mental simulation in the brain representation of meaningCited by: 6
Author(s): David Soto, Usman Ayub Sheikh, Ning Mei, Roberto Santana
Software Mentions: 1
Published: over 6 years ago
10.1148/ryai.2021200279
Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning–based Denoising Image FiltersCited by: 6
Author(s): Konstantinos Zormpas-Petridis, Nina Tunariu, Andra Curcean, Christina Messiou, Sebastian Curcean, David J. Collins, Julie Hughes, Yann Jamin, Dow‐Mu Koh, Matthew Blackledge
Software Mentions: 1
Published: about 5 years ago
10.1016/j.rsase.2020.100413
Detecting functional field units from satellite images in smallholder farming systems using a deep learning based computer vision approach: A case study from BangladeshCited by: 10
Author(s): Ruoyu Yang, Zia Ahmed, Urs Schulthess, Mustafa Kamal, Rahul Rai
Software Mentions: 1
Published: about 6 years ago
10.1038/sdata.2017.117
Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic featuresCited by: 1,551
Author(s): Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin Kirby, John Freymann, Keyvan Farahani, Christos Davatzikos
Software Mentions: 1
Published: about 9 years ago
10.1038/s41597-019-0312-2
A global wildfire dataset for the analysis of fire regimes and fire behaviourCited by: 106
Author(s): Tomàs Artés, Duarte Oom, Daniele de Rigo, Tracy Houston Durrant, Pieralberto Maianti, Liberta' Giorgio, Jesús San-Miguel-Ayanz
Software Mentions: 1
Published: almost 7 years ago
10.1038/s41597-020-0386-x
A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patientsCited by: 135
Author(s): Jianmin Zheng, Jianming Zhang, Sidy Danioko, Hai Yao, Hangyuan Guo, Cyril Rakovski
Software Mentions: 1
Published: over 6 years ago
10.1038/s41597-020-0440-8
A 12-Lead ECG database to identify origins of idiopathic ventricular arrhythmia containing 334 patientsCited by: 13
Author(s): Jianmin Zheng, Guohua Fu, Kyle Anderson, Huimin Chu, Cyril Rakovski
Software Mentions: 1
Published: over 6 years ago
10.1038/s41597-021-00827-9
The 10-m crop type maps in Northeast China during 2017–2019Cited by: 117
Author(s): Nanshan You, Jinwei Dong, Jianxi Huang, Guoming Du, Geli Zhang, Yingli He, Tong Yang, Yuanyuan Di, Xiangming Xiao
Software Mentions: 1
Published: almost 6 years ago