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: almost 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
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142 contributors with educational email addresses -
+20
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Repository owned by academic institution -
+15
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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/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: over 7 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: almost 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
10.1186/s12918-018-0546-1
In silico drug combination discovery for personalized cancer therapyCited by: 42
Author(s): Minji Jeon, Sunkyu Kim, Sungjoon Park, Heewon Lee, Jaewoo Kang
Software Mentions: 1
Published: over 8 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: almost 6 years ago
10.1128/AEM.00608-19
Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial CellCited by: 3
Author(s): Yutaka Yawata, Tatsunori Kiyokawa, Yasuhiko Kawamura, Tomohiro Hirayama, Kyosuke Takabe, Nobuhiko Nomura
Software Mentions: 1
Published: almost 7 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: about 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: about 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: about 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: over 5 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: over 6 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
10.1186/s12919-018-0140-y
Methods for detecting methylation by SNP interaction in GAW20 simulationCited by: 2
Author(s): E. Warwick Daw, James E. Hicks, Petra Lenzini, Shiow J. Lin, Judy Wang, Christine A. Williams, Ping An, Michael A. Province, Aldi T. Kraja
Software Mentions: 1
Published: about 8 years ago
10.3390/ijms21207501
How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS DataCited by: 3
Author(s): Magdalena Góralska, Jan Bińkowski, Natalia Lenarczyk, Anna Bienias, Agnieszka Grądzielewska, Ilona Czyczyło-Mysza, Kamila Kapłoniak, Stefan Stojałowski, Beata Myśków
Software Mentions: 1
Published: almost 6 years ago
10.1186/s12883-018-1198-x
The Norwegian Cognitive impairment after stroke study (Nor-COAST): study protocol of a multicentre, prospective cohort studyCited by: 33
Author(s): Pernille Thingstad, Torunn Askim, Mona K. Beyer, Geir Bråthen, Hanne Ellekjær, Hege Ihle‐Hansen, Anne Brita Knapskog, Stian Lydersen, Ragnhild Munthe-Kaas, Halvor Næss, Sarah T. Pendlebury, Yngve Müller Seljeseth, Ingvild Saltvedt
Software Mentions: 1
Published: almost 8 years ago
10.1186/s12882-020-01980-w
Changing relative risk of clinical factors for hospital-acquired acute kidney injury across age groups: a retrospective cohort studyCited by: 5
Author(s): Lijuan Wu, Yong Hu, Xiangzhou Zhang, Weiqi Chen, Alan Yu, John A. Kellum, Lemuel R. Waitman, Мэй Лю
Software Mentions: 1
Published: about 6 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: about 5 years ago
10.1186/s12874-021-01242-9
Waist circumference prediction for epidemiological research using gradient boosted treesCited by: 4
Author(s): Weihong Zhou, Spencer Maxwell Eckler, Andrew Barszczyk, Alex Waese-Perlman, Yingjie Wang, Xiaoping Gu, Feng Zhang, Yongjun Peng, Kang Lee
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: over 5 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: almost 8 years ago
10.1186/s12911-015-0206-y
Prediction of delayed graft function after kidney transplantation: comparison between logistic regression and machine learning methodsCited by: 50
Author(s): Alexander Decruyenaere, Philippe Decruyenaere, Patrick Peeters, Frank Vermassen, Tom Dhaene, Ivo Couckuyt
Software Mentions: 1
Published: almost 11 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: over 6 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
10.1007/s10439-020-02591-0
Quantification of Myocardial Blood Flow by Machine Learning Analysis of Modified Dual Bolus MRI ExaminationCited by: 2
Author(s): Minna Husso, Isaac O. Afara, Mikko J. Nissi, Antti Kuivanen, Paavo Halonen, Miikka Tarkia, Jarmo Teuho, Virva Saunavaara, Pauli Vainio, Petri Sipola, Hannu Manninen, Seppo Ylä‐Herttuala, Juhani Knuuti, Juha Töyräs
Software Mentions: 1
Published: about 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: almost 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: about 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: over 9 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: over 5 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: almost 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: almost 7 years ago
10.1186/s12911-020-01215-w
Identification of risk factors for patients with diabetes: diabetic polyneuropathy case studyCited by: 11
Author(s): Oleg G. Metsker, Kirill Magoev, Alexey N. Yakovlev, S. N. Yanishevskiy, Georgy Kopanitsa, Sergey V. Kovalchuk, Valeria V. Krzhizhanovskaya
Software Mentions: 1
Published: about 6 years ago
10.1109/TBME.2018.2890167
Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical TissueCited by: 23
Author(s): Yutao Ma, Tao Xu, Xiaolei Huang, Xiaofang Wang, Canyu Li, Jason Jerwick, Naichang Yuan, Xiaomao Zeng, Bo Wang, Yihong Wang, Zhan Zhang, Xiaoan Zhang, Chao Zhou
Software Mentions: 1
Published: about 7 years ago
10.1186/s12911-021-01514-w
Bayesian network models with decision tree analysis for management of childhood malaria in MalawiCited by: 4
Author(s): Sanya Bathla Taneja, Gerald P. Douglas, Gregory F. Cooper, Marian G. Michaels, Marek J. Drużdżel, Shyam Visweswaran
Software Mentions: 1
Published: over 5 years ago
10.1186/s40192-015-0042-z
Machine learning approaches for elastic localization linkages in high-contrast composite materialsCited by: 52
Author(s): Ruoqian Liu, Yuksel C. Yabansu, Ankit Agrawal, Surya R. Kalidindi, Alok Choudhary
Software Mentions: 1
Published: almost 11 years ago
10.1155/2016/5080746
Evaluation and Verification of the Global Rapid Identification of Threats System for Infectious Diseases in Textual Data SourcesCited by: 7
Author(s): Andy Huff, Nathan Breit, Talli Allen, Karissa Whiting, Christopher Kiley
Software Mentions: 1
Published: over 10 years ago
10.1186/s12911-021-01506-w
Machine learning predicts mortality based on analysis of ventilation parameters of critically ill patients: multi-centre validationCited by: 8
Author(s): Behrooz Mamandipoor, Fernando Frutos‐Vivar, Óscar Peñuelas, Richard Rezar, Konstantinos Raymondos, Alfonso Muriel, Bin Du, Arnaud W. Thille, Fernando Ríos, Marco González, Lorenzo del-Sorbo, María del Carmen Marín, Bruno Valle Pinheiro, Marco Antonio Soares, Nicolás Nín, Salvatore Maurizio Maggiore, Andrew D. Bersten, Malte Kelm, Raphael Romano Bruno, Pravin Amin, Nahit Çakar, Gee Young Suh, Fékri Abroug, Manuel Jibaja, Dimitros Matamis, Amine Ali Zeggwagh, Yuda Sutherasan, Antonio Anzueto, Bernhard Wernly, Andrés Esteban, Christian Jung, Venet Osmani
Software Mentions: 1
Published: over 5 years ago
10.1001/jamanetworkopen.2019.14051
Trends and Focus of Machine Learning Applications for Health ResearchCited by: 39
Author(s): Brett K. Beaulieu‐Jones, Samuel G. Finlayson, Corey Chivers, Irene Chen, Matthew B. A. McDermott, Jaz Kandola, Adrian V. Dalca, Andrew L. Beam, Madalina Fiterau, Tristan Naumann
Software Mentions: 1
Published: almost 7 years ago
10.1001/jamanetworkopen.2020.6653
Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With DepressionCited by: 40
Author(s): Pranav Rajpurkar, Jingbo Yang, Nathan Dass, Vinjai Vale, Arielle S. Keller, Jeremy Irvin, Zachary Taylor, Sanjay Basu, Andrew Y. Ng, Leanne M. Williams
Software Mentions: 1
Published: about 6 years ago
10.1001/jamanetworkopen.2020.20485
Association of Mobile Phone Location Data Indications of Travel and Stay-at-Home Mandates With COVID-19 Infection Rates in the USCited by: 141
Author(s): Song Gao, Jinmeng Rao, Yuhao Kang, Yunlei Liang, Jake Kruse, Dörte Döpfer, Ajay K. Sethi, J. Reyes, Brian S. Yandell, Jonathan A. Patz
Software Mentions: 1
Published: almost 6 years ago
10.1001/jamanetworkopen.2020.26750
Predictive Modeling for Perinatal Mortality in Resource-Limited SettingsCited by: 30
Author(s): Vivek V. Shukla, Barry Eggleston, Namasivayam Ambalavanan, Elizabeth M McClure, Musaku Mwenechanya, Elwyn Chomba, Carl Bose, Melissa Bauserman, Antoinette Tshefu, Shivaprasad S. Goudar, Richard Derman, Ana Garcés, Nancy F. Krebs, Sarah Saleem, Robert L. Goldenberg, Archana Patel, Patricia L. Hibberd, Fabian Esamai, Sherri Bucher, Edward A. Liechty, Marion Koso‐Thomas, Waldemar A. Carlo
Software Mentions: 1
Published: almost 6 years ago
10.1001/jamanetworkopen.2020.30939
Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy SpecimensCited by: 26
Author(s): Jon N. Marsh, Ta‐Chiang Liu, Parker C. Wilson, S. Joshua Swamidass, Joseph P. Gaut
Software Mentions: 1
Published: over 5 years ago
10.1001/jamanetworkopen.2020.36220
Machine Learning of Patient Characteristics to Predict Admission Outcomes in the Undiagnosed Diseases NetworkCited by: 2
Author(s): Hadi Amiri, Isaac S. Kohane
Software Mentions: 1
Published: over 5 years ago
10.1001/jamanetworkopen.2021.7746
Genomic Epidemiology of SARS-CoV-2 Infection During the Initial Pandemic Wave and Association With Disease SeverityCited by: 27
Author(s): Frank Esper, Yu‐Wei Cheng, Thamali M Adhikari, Zheng Jin Tu, Derek Li, Erik A Li, Daniel H. Farkas, Gary W. Procop, Jennifer S. Ko, Timothy A. Chan, Lara Jehi, Brian P. Rubin, Jing Li
Software Mentions: 1
Published: over 5 years ago
10.1186/s12911-018-0676-9
Leveraging auxiliary measures: a deep multi-task neural network for predictive modeling in clinical researchCited by: 7
Author(s): Xiangrui Li, Dongxiao Zhu, Phillip D. Levy
Software Mentions: 1
Published: almost 8 years ago
10.1001/jamapediatrics.2020.5227
Translation of a Host Blood RNA Signature Distinguishing Bacterial From Viral Infection Into a Platform Suitable for Development as a Point-of-Care TestCited by: 27
Author(s): Ivana Pennisi, Jesús Rodríguez-Manzano, Ahmad Moniri, Myrsini Kaforou, Jethro Herberg, Michael Levin, Pantelis Georgiou
Software Mentions: 1
Published: over 5 years ago
10.1093/jamiaopen/ooaa001
Efficient goal attainment and engagement in a care manager system using unstructured notesCited by: 0
Author(s): Sara Rosenthal, Subhro Das, Pei-Yun Sabrina Hsueh, Ken Barker, Ching-Hua Chen
Software Mentions: 1
Published: over 6 years ago
10.1172/jci.insight.93344
Endothelium-derived extracellular vesicles promote splenic monocyte mobilization in myocardial infarctionCited by: 70
Author(s): Naveed Akbar, Janet E. Digby, Thomas J. Cahill, Aniket Tavare, Alastair Corbin, Sonia Saluja, Sam Dawkins, Laurienne Edgar, Nadiia Rawlings, Klemen Žiberna, Eileen McNeill, Errin Johnson, Alaa A. A. Aljabali, Rebecca Dragovic, Mala Rohling, T. Grant Belgard, Irina A. Udalova, David R. Greaves, Keith M. Channon, Paul R. Riley, Daniel C. Anthony, R P Choudhury
Software Mentions: 1
Published: almost 9 years ago
10.1172/jci.insight.144779
Deep learning–based molecular morphometrics for kidney biopsiesCited by: 25
Author(s): Marina Zimmermann, Martin Klaus, Milagros Wong, Ann-Katrin Thebille, Lukas Gernhold, Christoph Kuppe, Maurice Halder, Jennifer Kranz, Nicola Wanner, Fabian Braun, Sonia Wulf, Thorsten Wiech, Ulf Panzer, Christian Krebs, Elion Hoxha, Rafael Kramann, Tobias B. Huber, Stefan Bonn, Victor G. Puelles
Software Mentions: 1
Published: over 5 years ago
10.3390/ijms22136791
Using RNA-Sequencing Data to Examine Tissue-Specific Garlic MicrobiomesCited by: 7
Author(s): Yeonhwa Jo, Chang–Gi Back, Kook‐Hyung Kim, Hyosub Chu, Jeong Hun Lee, Sang Hyun Moh, Won Kyong Cho
Software Mentions: 1
Published: about 5 years ago
10.1200/CCI.17.00065
Deep Learning–Based Survival Analysis Identified Associations Between Molecular Subtype and Optimal Adjuvant Treatment of Patients With Gastric CancerCited by: 13
Author(s): Jeeyun Lee, Ji Yeong An, Min Gew Choi, Se Hoon Park, Seung Tae Kim, Jun Ho Lee, Tae Sung Sohn, Jae Moon Bae, Sung Hoon Kim, Hyuk Lee, Byung-Hoon Min, Jae J. Kim, Woo Kyoung Jeong, Dongil Choi, Kyoung‐Mee Kim, Won Ki Kang, Mi‐Jung Kim, Sung Wook Seo
Software Mentions: 1
Published: almost 8 years ago
10.1200/CCI.19.00136
Predicting Lung Cancer Survival Using Probabilistic Reclassification of TNM Editions With a Bayesian NetworkCited by: 3
Author(s): Melle Sieswerda, Iñigo Bermejo, Gijs Geleijnse, Mieke J. Aarts, Valery Lemmens, Dirk De Ruysscher, André Dekker, Xander Verbeek
Software Mentions: 1
Published: almost 6 years ago
10.1186/s12911-020-01297-6
Combining structured and unstructured data for predictive models: a deep learning approachCited by: 80
Author(s): Dongdong Zhang, Changchang Yin, Jucheng Zeng, Xiaohui Yuan, Ping Zhang
Software Mentions: 1
Published: almost 6 years ago
10.1155/2019/1537568
Tracing Geographical Origins of Teas Based on FT-NIR Spectroscopy: Introduction of Model Updating and Imbalanced Data Handling ApproachesCited by: 16
Author(s): Xiaopeng Hong, Xian-Shu Fu, Zhengliang Wang, Li Zhang, Xiaoping Yu, Zihong Ye
Software Mentions: 1
Published: over 7 years ago
10.1074/jbc.M117.810945
Single-subunit oligosaccharyltransferases of Trypanosoma brucei display different and predictable peptide acceptor specificitiesCited by: 13
Author(s): Anders Jinnelöv, Liaqat Ali, Michele Tinti, Maria Lucia S. Güther, Michael A. J. Ferguson
Software Mentions: 1
Published: almost 9 years ago
10.3390/ijms22147721
Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 PredictionCited by: 8
Author(s): Yeeun Lee, Seungyoon Nam
Software Mentions: 1
Published: about 5 years ago
10.1117/1.JBO.24.7.071606
Machine learning approach for rapid and accurate estimation of optical properties using spatial frequency domain imagingCited by: 36
Author(s): Swapnesh Panigrahi, Sylvain Gioux
Software Mentions: 1
Published: over 7 years ago
10.1186/s12911-020-01380-y
Isotypes of autoantibodies against novel differential 4-hydroxy-2-nonenal-modified peptide adducts in serum is associated with rheumatoid arthritis in Taiwanese womenCited by: 7
Author(s): Kai-Leun Tsai, Che-Chang Chang, Yu‐Sheng Chang, Yiying Lu, I-Jung Tsai, Jinhua Chen, Sheng-Hong Lin, Chih-Chun Tai, Yi-Fang Lin, Hui‐Wen Chang, Chun–Ming Lin, Emily Chia-Yu Su
Software Mentions: 1
Published: over 5 years ago
10.1186/s13326-020-00221-1
Neural side effect discovery from user credibility and experience-assessed online health discussionsCited by: 1
Author(s): Van-Hoang Nguyen, Kazunari Sugiyama, Min-Yen Kan, Kishaloy Halder
Software Mentions: 1
Published: about 6 years ago
10.7150/jca.37006
A Panel of Urinary Long Non-coding RNAs Differentiate Bladder Cancer from UrocystitisCited by: 24
Author(s): Xiao Yu, Ruiwei Wang, Chenglin Han, Zilong Wang, Xunbo Jin
Software Mentions: 1
Published: over 6 years ago
10.1186/s12911-020-01131-z
AutoDiscern: rating the quality of online health information with hierarchical encoder attention-based neural networksCited by: 17
Author(s): Laura Kinkead, Ahmed Allam, Michael Krauthammer
Software Mentions: 1
Published: about 6 years ago
10.3390/jcdd8060065
Machine Learning for Predicting Mortality in Transcatheter Aortic Valve Implantation: An Inter-Center Cross Validation StudyCited by: 3
Author(s): Marco Mamprin, Ricardo R. Lopes, Jo M. Zelis, Pim A.L. Tonino, Martijn S. van Mourik, Marije M. Vis, Svitlana Zinger, Bas A.J.M. de Mol, Peter H. N. de With
Software Mentions: 1
Published: about 5 years ago
10.3390/ani11092660
Training and Validating a Machine Learning Model for the Sensor-Based Monitoring of Lying Behavior in Dairy Cows on Pasture and in the BarnCited by: 9
Author(s): Lara Schmeling, Golnaz Elmamooz, Phan Thai Hoang, Anastasiia Kozar, Daniela Nicklas, Michael Sünkel, S. Thurner, E. Rauch
Software Mentions: 1
Published: almost 5 years ago
10.1021/acs.jcim.1c00451
ChemBioSim: Enhancing Conformal Prediction of In Vivo Toxicity by Use of Predicted BioactivitiesCited by: 12
Author(s): Marina Garcia de Lomana, Andrea Morger, Ulf Norinder, Roland Buesen, Robert Landsiedel, Andrea Volkamer, Johannes Kirchmair, Miriam Mathea
Software Mentions: 1
Published: about 5 years ago
10.1021/acs.jctc.0c00961
Per|Mut: Spatially Resolved Hydration Entropies from Atomistic SimulationsCited by: 12
Author(s): Leonard P. Heinz, Helmut Grubmüller
Software Mentions: 1
Published: over 5 years ago
10.1186/s12911-021-01562-2
On the predictability of postoperative complications for cancer patients: a Portuguese cohort studyCited by: 3
Author(s): Daniel Gonçalves, Rui Henriques, Lúcio Lara Santos, Rafael S. Costa
Software Mentions: 1
Published: about 5 years ago
10.3390/ijms22158027
PON-Sol2: Prediction of Effects of Variants on Protein SolubilityCited by: 9
Author(s): Yang Yang, Lianjie Zeng, Mauno Vihinen
Software Mentions: 1
Published: about 5 years ago
10.1186/s13321-016-0124-8
GPURFSCREEN: a GPU based virtual screening tool using random forest classifierCited by: 18
Author(s): P. B. Jayaraj, Mathias K. Ajay, M. Nufail, G Gopakumar, U. C. Abdul Jaleel
Software Mentions: 1
Published: over 10 years ago
10.1186/s12911-019-1008-4
Novel prognostication of patients with spinal and pelvic chondrosarcoma using deep survival neural networksCited by: 19
Author(s): Sung Mo Ryu, Sung Wook Seo, Sun-Ho Lee
Software Mentions: 1
Published: over 6 years ago
10.1186/s12911-019-0782-3
Identifying peer experts in online health forumsCited by: 15
Author(s): V. G. Vinod Vydiswaran, Manoj Reddy
Software Mentions: 1
Published: over 7 years ago
10.1186/s13321-018-0268-9
Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screeningCited by: 13
Author(s): Rafaela Gladysz, Fábio Mendes dos Santos, Wilfried Langenaeker, Gert Thijs, Koen Augustyns, Hans De Winter
Software Mentions: 1
Published: over 8 years ago
10.1186/s13321-018-0275-x
Finding the molecular scaffold of nuclear receptor inhibitors through high-throughput screening based on proteochemometric modellingCited by: 5
Author(s): Tianyi Qiu, Dingfeng Wu, Jingxuan Qiu, Zhiwei Cao
Software Mentions: 1
Published: over 8 years ago
10.1186/s13321-018-0281-z
Effect of missing data on multitask prediction methodsCited by: 27
Author(s): Antonio de la Vega de León, Beining Chen, Valerie J. Gillet
Software Mentions: 1
Published: over 8 years ago
10.1186/s12911-021-01489-8
Early warning of citric acid overdose and timely adjustment of regional citrate anticoagulation based on machine learning methodsCited by: 6
Author(s): Huan Chen, Yingying Ma, Na Hong, Hao Wang, Longxiang Su, Chun Li, Jie He, Huizhen Jiang, Yun Long, Weiguo Zhu
Software Mentions: 1
Published: about 5 years ago
10.1186/s13321-019-0364-5
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound imagesCited by: 40
Author(s): Isidro Cortés-Ciriano, Andreas Bender
Software Mentions: 1
Published: about 7 years ago
10.1186/s13321-019-0368-1
Multi-channel PINN: investigating scalable and transferable neural networks for drug discoveryCited by: 17
Author(s): Munhwan Lee, Hye-Yeon Kim, Hyunwhan Joe, Hong-Gee Kim
Software Mentions: 1
Published: about 7 years ago
10.1186/s13321-018-0310-y
Implicit-descriptor ligand-based virtual screening by means of collaborative filteringCited by: 10
Author(s): Raghuram Srinivas, Pavel V. Klimovich, Eric C. Larson
Software Mentions: 1
Published: almost 8 years ago
10.1186/s13321-020-0413-0
Evaluation of deep and shallow learning methods in chemogenomics for the prediction of drugs specificityCited by: 24
Author(s): Benoit Playe, Véronique Stoven
Software Mentions: 1
Published: over 6 years ago
10.2196/28361
Developing a time-adaptive prediction model for out-of-hospital cardiac arrest: Results from a nationwide cohort study in Korea (Preprint)Cited by: 2
Author(s): Ji Woong
Software Mentions: 1
Published: over 5 years ago
10.1186/s13321-020-00434-7
Assessing the information content of structural and protein–ligand interaction representations for the classification of kinase inhibitor binding modes via machine learning and active learningCited by: 14
Author(s): Raquel Rodríguez-Pérez, Filip Miljković, Jürgen Bajorath
Software Mentions: 1
Published: over 6 years ago
10.1186/s12911-020-01326-4
Hyperchloremia in critically ill patients: association with outcomes and prediction using electronic health record dataCited by: 9
Author(s): Pete Yeh, Yiheng Pan, L. Nelson Sanchez-Pinto, Yuan Luo
Software Mentions: 1
Published: almost 6 years ago
10.1186/s13321-020-00452-5
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumerationCited by: 18
Author(s): Ryosuke Shibukawa, Shoichi Ishida, Kazuki Yoshizoe, Kiyotaka Wasa, Kiyosei Takasu, Yasushi Okuno, Kei Terayama, Koji Tsuda
Software Mentions: 1
Published: about 6 years ago
10.1186/s13321-020-00473-0
Memory-assisted reinforcement learning for diverse molecular de novo designCited by: 47
Author(s): Thomas Blaschke, Ola Engkvist, Jürgen Bajorath, Hongming Chen
Software Mentions: 1
Published: almost 6 years ago
10.2196/11756
Understanding User Experience: Exploring Participants’ Messages With a Web-Based Behavioral Health Intervention for Adolescents With Chronic PainCited by: 5
Author(s): Annie Chen, Aarti Swaminathan, William R. Kearns, Nicole M. Alberts, Emily F. Law, Tonya M. Palermo
Software Mentions: 1
Published: over 7 years ago
10.1186/s13321-021-00499-y
Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification modelsCited by: 10
Author(s): Annachiara Tinivella, Luca Pinzi, Giulio Rastelli
Software Mentions: 1
Published: over 5 years ago
10.1186/s12911-019-0781-4
Clinical text classification with rule-based features and knowledge-guided convolutional neural networksCited by: 76
Author(s): Yao Liang, Chengsheng Mao, Yuan Luo
Software Mentions: 1
Published: over 7 years ago
10.3390/ani11010050
Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour ClassificationCited by: 7
Author(s): Jennifer Salau, Jan Haas, Wolfgang Junge, Georg Thaller
Software Mentions: 1
Published: over 5 years ago
10.1186/s12911-021-01582-y
Privacy-preserving dataset combination and Lasso regression for healthcare predictionsCited by: 12
Author(s): Marie Beth van Egmond, Gabriele Spini, Onno van der Galiën, Arne IJpma, Thijs Veugen, Wessel Kraaij, Alex Sangers, Thomas Rooijakkers, Peter Langenkamp, Bart Kamphorst, Natasja van de L’Isle, Milena Kooij-Janic
Software Mentions: 1
Published: almost 5 years ago
10.1186/s12911-021-01591-x
Improvement of APACHE II score system for disease severity based on XGBoost algorithmCited by: 8
Author(s): Yan Luo, Zhiyu Wang, Cong Wang
Software Mentions: 1
Published: about 5 years ago
10.3390/jcm7090277
Development of a Prediction Model for Colorectal Cancer among Patients with Type 2 Diabetes Mellitus Using a Deep Neural NetworkCited by: 15
Author(s): Meng-Hsuen Hsieh, Li‐Min Sun, Cheng‐Li Lin, Meng-Ju Hsieh, Kyle Sun, Chung Y. Hsu, An‐Kuo Chou, Chia Hung Kao
Software Mentions: 1
Published: almost 8 years ago
10.3390/jcm7090240
An Artificial Neural Network Model for Predicting Successful Extubation in Intensive Care UnitsCited by: 38
Author(s): Meng-Hsuen Hsieh, Meng-Ju Hsieh, Chin‐Ming Chen, Chih-Chang Hsieh, Chien‐Ming Chao, Chih‐Cheng Lai
Software Mentions: 1
Published: about 8 years ago