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Wyszukujesz frazę ""Machine Learning"" wg kryterium: Temat


Tytuł :
Longitudinal self-supervised learning.
Autorzy :
Zhao Q; Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA.
Liu Z; Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA.
Adeli E; Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA.
Pohl KM; Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA 94305, USA; Center for Biomedical Sciences, SRI International, Menlo Park, CA 95025, USA. Electronic address: .
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Źródło :
Medical image analysis [Med Image Anal] 2021 Jul; Vol. 71, pp. 102051. Date of Electronic Publication: 2021 Apr 04.
Typ publikacji :
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
MeSH Terms :
Magnetic Resonance Imaging*
Supervised Machine Learning*
Brain/diagnostic imaging ; Humans ; Machine Learning
Czasopismo naukowe
Tytuł :
Regression plane concept for analysing continuous cellular processes with machine learning.
Autorzy :
Szkalisity A; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary.; Department of Anatomy and Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Piccinini F; Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Meldola, FC, Italy.
Beleon A; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary.
Balassa T; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary.
Varga IG; Institute of Genetics, Biological Research Center (BRC), Szeged, Hungary.
Migh E; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary.
Molnar C; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary.
Paavolainen L; Institute for Molecular Medicine Finland-FIMM, Helsinki Institute of Life Science-HiLIFE, University of Helsinki, Helsinki, Finland.
Timonen S; Institute for Molecular Medicine Finland-FIMM, Helsinki Institute of Life Science-HiLIFE, University of Helsinki, Helsinki, Finland.
Banerjee I; Indian Institute of Science Education and Research (IISER), Mohali, India.
Ikonen E; Department of Anatomy and Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Yamauchi Y; School of Cellular and Molecular Medicine, University of Bristol, BS8 1TD University Walk, Bristol, UK.
Ando I; Institute of Genetics, Biological Research Center (BRC), Szeged, Hungary.
Peltonen J; Faculty of Information Technology and Communication Sciences, Tampere University, FI-33014 Tampere University, Tampere, Finland.; Department of Computer Science, Aalto University, Aalto, Finland.
Pietiäinen V; Institute for Molecular Medicine Finland-FIMM, Helsinki Institute of Life Science-HiLIFE, University of Helsinki, Helsinki, Finland.
Honti V; Institute of Genetics, Biological Research Center (BRC), Szeged, Hungary.
Horvath P; Synthetic and Systems Biology Unit, Biological Research Centre (BRC), Szeged, Hungary. .; Institute for Molecular Medicine Finland-FIMM, Helsinki Institute of Life Science-HiLIFE, University of Helsinki, Helsinki, Finland. .; Single-Cell Technologies Ltd., Szeged, Hungary. .
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Źródło :
Nature communications [Nat Commun] 2021 May 05; Vol. 12 (1), pp. 2532. Date of Electronic Publication: 2021 May 05.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Biological Phenomena*
Cell Physiological Phenomena*
Machine Learning*
Animals ; Carcinoma, Hepatocellular ; Cell Cycle ; Cell Differentiation ; Cell Line, Tumor ; Drosophila melanogaster ; Humans ; Membrane Proteins ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Domain adaptation and self-supervised learning for surgical margin detection.
Autorzy :
Santilli AML; School of Computing, Queen's University, Ontario, Canada. .
Jamzad A; School of Computing, Queen's University, Ontario, Canada.
Sedghi A; School of Computing, Queen's University, Ontario, Canada.
Kaufmann M; Department of Surgery, Queen's University, Ontario, Canada.
Logan K; Department of Pathology and Molecular Medicine, Queen's University, Ontario, Canada.
Wallis J; Department of Pathology and Molecular Medicine, Queen's University, Ontario, Canada.
Ren KYM; Department of Pathology and Molecular Medicine, Queen's University, Ontario, Canada.
Janssen N; School of Computing, Queen's University, Ontario, Canada.
Merchant S; Department of Surgery, Queen's University, Ontario, Canada.
Engel J; Department of Surgery, Queen's University, Ontario, Canada.
McKay D; Department of Surgery, Queen's University, Ontario, Canada.
Varma S; Department of Pathology and Molecular Medicine, Queen's University, Ontario, Canada.
Wang A; Department of Pathology and Molecular Medicine, Queen's University, Ontario, Canada.
Fichtinger G; School of Computing, Queen's University, Ontario, Canada.
Rudan JF; Department of Surgery, Queen's University, Ontario, Canada.
Mousavi P; School of Computing, Queen's University, Ontario, Canada.
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Źródło :
International journal of computer assisted radiology and surgery [Int J Comput Assist Radiol Surg] 2021 May; Vol. 16 (5), pp. 861-869. Date of Electronic Publication: 2021 May 06.
Typ publikacji :
Journal Article
MeSH Terms :
Margins of Excision*
Supervised Machine Learning*
Breast/*surgery
Breast Neoplasms/*surgery
Mastectomy, Segmental/*methods
Skin/*diagnostic imaging
Algorithms ; Area Under Curve ; Breast Neoplasms/diagnostic imaging ; Calibration ; Carcinoma, Basal Cell/diagnostic imaging ; Female ; Humans ; Machine Learning ; Mastectomy ; Operating Rooms ; Reproducibility of Results ; Sensitivity and Specificity ; Skin Neoplasms/diagnostic imaging ; Stochastic Processes
Czasopismo naukowe
Tytuł :
Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology.
Autorzy :
Fagerholm U; Prosilico AB, Lännavägen 7, SE-141 45 Huddinge, Sweden.
Hellberg S; Prosilico AB, Lännavägen 7, SE-141 45 Huddinge, Sweden.
Spjuth O; Prosilico AB, Lännavägen 7, SE-141 45 Huddinge, Sweden.; Department of Pharmaceutical Biosciences and Science for Life Laboratory, Uppsala University, Box 591, SE-751 24 Uppsala, Sweden.
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Źródło :
Molecules (Basel, Switzerland) [Molecules] 2021 Apr 28; Vol. 26 (9). Date of Electronic Publication: 2021 Apr 28.
Typ publikacji :
Journal Article
MeSH Terms :
Machine Learning*
Models, Biological*
Pharmaceutical Preparations*/administration & dosage
Pharmaceutical Preparations*/chemistry
Pharmacokinetics*
Administration, Oral ; Biological Availability ; Computer Simulation ; Drug Evaluation, Preclinical ; Humans ; Quantitative Structure-Activity Relationship ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.
Autorzy :
Mackey TK; Department of Anesthesiology and Division of Infectious Disease and Global Public Health, University of California, San Diego, San Diego, CA 92037, USA; Department of Healthcare Research and Policy, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA; S-3 Research, San Diego, CA, USA. Electronic address: .
Purushothaman V; Department of Family Medicine and Public Health, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA.
Haupt M; Department of Cognitive Science, University of California, San Diego, San Diego, CA 92037, USA.
Nali MC; Department of Anesthesiology and Division of Infectious Disease and Global Public Health, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA; S-3 Research, San Diego, CA, USA.
Li J; Department of Healthcare Research and Policy, University of California, San Diego, San Diego, CA 92037, USA; Global Health Policy Institute, San Diego, CA, USA; S-3 Research, San Diego, CA, USA.
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Źródło :
The Lancet. Digital health [Lancet Digit Health] 2021 Feb; Vol. 3 (2), pp. e72-e75.
Typ publikacji :
Journal Article
MeSH Terms :
Communication*
Hydroxychloroquine*
Social Media*
Unsupervised Machine Learning*
COVID-19/drug therapy ; Humans ; Internet Use ; Machine Learning ; Quackery
Czasopismo naukowe
Tytuł :
Designing individual-specific and trial-specific models to accurately predict the intensity of nociceptive pain from single-trial fMRI responses.
Autorzy :
Lin Q; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China; Department of Brain Functioning Research, The Seventh Hospital of Hangzhou, 305 Tianmushan Road, Hangzhou, Zhejiang, China.
Huang G; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China.
Li L; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China.
Zhang L; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China.
Liang Z; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China.
Anter AM; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China.
Zhang Z; School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, Guangdong 518060, China; Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, Shenzhen, Guangdong 518060, China; Peng Cheng Laboratory, Shenzhen, Guangdong 518055, China. Electronic address: .
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Źródło :
NeuroImage [Neuroimage] 2021 Jan 15; Vol. 225, pp. 117506. Date of Electronic Publication: 2020 Oct 27.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Supervised Machine Learning*
Brain/*diagnostic imaging
Nociceptive Pain/*diagnostic imaging
Adult ; Cluster Analysis ; Female ; Functional Neuroimaging ; Humans ; Least-Squares Analysis ; Machine Learning ; Magnetic Resonance Imaging ; Male ; Nociceptive Pain/physiopathology ; Pain Measurement ; Young Adult
Czasopismo naukowe
Tytuł :
Application of Machine Learning Techniques to Predict Binding Affinity for Drug Targets: A Study of Cyclin-Dependent Kinase 2.
Autorzy :
Bitencourt-Ferreira G; Laboratory of Computational Systems Biology. Pontifical Catholic University of Rio Grande do Sul (PUCRS). Av. Ipiranga, 6681 Porto Alegre/RS 90619-900 , Brazil.
Duarte da Silva A; Specialization Program in Bioinformatics. Pontifical Catholic University of Rio Grande do Sul (PUCRS). Av. Ipiranga, 6681 Porto Alegre/RS 90619-900, Brazil.
Filgueira de Azevedo W Jr; Laboratory of Computational Systems Biology. Pontifical Catholic University of Rio Grande do Sul (PUCRS). Av. Ipiranga, 6681 Porto Alegre/RS 90619-900 , Brazil.
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Źródło :
Current medicinal chemistry [Curr Med Chem] 2021; Vol. 28 (2), pp. 253-265.
Typ publikacji :
Journal Article; Review
MeSH Terms :
Machine Learning*
Cyclin-Dependent Kinase 2 ; Humans ; Ligands ; Molecular Docking Simulation ; Pharmaceutical Preparations ; Protein Binding ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states.
Autorzy :
Sabbagh D; Université Paris-Saclay, Inria, CEA, Palaiseau, France; Inserm, UMRS-942, Paris Diderot University, Paris, France; Department of Anaesthesiology and Critical Care, Lariboisière Hospital, Assistance Publique Hôpitaux de Paris, Paris, France. Electronic address: .
Ablin P; Université Paris-Saclay, Inria, CEA, Palaiseau, France.
Varoquaux G; Université Paris-Saclay, Inria, CEA, Palaiseau, France.
Gramfort A; Université Paris-Saclay, Inria, CEA, Palaiseau, France.
Engemann DA; Université Paris-Saclay, Inria, CEA, Palaiseau, France; Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurology, D-04103, Leipzig, Germany. Electronic address: .
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Źródło :
NeuroImage [Neuroimage] 2020 Nov 15; Vol. 222, pp. 116893. Date of Electronic Publication: 2020 May 18.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Brain Waves*/physiology
Cerebral Cortex*/physiology
Machine Learning*
Models, Theoretical*
Electroencephalography/*methods
Magnetoencephalography/*methods
Adult ; Computer Simulation ; Electromyography ; Humans ; Regression Analysis ; Signal Processing, Computer-Assisted ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Supervised learning on phylogenetically distributed data.
Autorzy :
Layne E; School of Computer Science, McGill, Montreal, QC H3A 0E9, Canada.
Dort EN; Department of Forestry and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Hamelin R; Department of Forestry and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Li Y; School of Computer Science, McGill, Montreal, QC H3A 0E9, Canada.
Blanchette M; School of Computer Science, McGill, Montreal, QC H3A 0E9, Canada.
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Źródło :
Bioinformatics (Oxford, England) [Bioinformatics] 2020 Dec 30; Vol. 36 (Suppl_2), pp. i895-i902.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Machine Learning*
Neural Networks, Computer*
Phylogeny ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition.
Autorzy :
Raschka S; University of Wisconsin-Madison, Department of Statistics, United States. Electronic address: .
Kaufman B; University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics, United States.
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Źródło :
Methods (San Diego, Calif.) [Methods] 2020 Aug 01; Vol. 180, pp. 89-110. Date of Electronic Publication: 2020 Jul 06.
Typ publikacji :
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Review
MeSH Terms :
Artificial Intelligence*
Machine Learning*
Drug Discovery/*methods
Receptors, G-Protein-Coupled/*chemistry
Deep Learning ; Ligands ; Neural Networks, Computer ; Software ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Analysis of Cattle Social Transitional Behaviour: Attraction and Repulsion.
Autorzy :
Xu H; School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Kensington, NSW 2052, Australia.
Li S; Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marsfield, NSW 2122, Australia.
Lee C; Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Armidale, NSW 2350, Australia.
Ni W; Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marsfield, NSW 2122, Australia.
Abbott D; Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marsfield, NSW 2122, Australia.
Johnson M; Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Marsfield, NSW 2122, Australia.
Lea JM; Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Armidale, NSW 2350, Australia.
Yuan J; School of Electrical Engineering and Telecommunications, University of New South Wales, High St, Kensington, NSW 2052, Australia.
Campbell DLM; Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Armidale, NSW 2350, Australia.
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Źródło :
Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Sep 18; Vol. 20 (18). Date of Electronic Publication: 2020 Sep 18.
Typ publikacji :
Journal Article
MeSH Terms :
Algorithms*
Machine Learning*
Social Behavior*
Animals ; Cattle ; Cluster Analysis ; Unsupervised Machine Learning
Czasopismo naukowe
Tytuł :
Cross Lingual Sentiment Analysis: A Clustering-Based Bee Colony Instance Selection and Target-Based Feature Weighting Approach.
Autorzy :
Mohammed Almansor MA; School of Information and Communication Engineering, Zhongshan Institute, University of Electronic Science and Technology of China, Chengdu 611731, China.
Zhang C; School of Information and Communication Engineering, Zhongshan Institute, University of Electronic Science and Technology of China, Chengdu 611731, China.; School of Electronic Information, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China.
Khan W; Department of Computer Science, Liverpool John Moores University, Liverpool L33AF, UK.
Hussain A; Department of Computer Science, Liverpool John Moores University, Liverpool L33AF, UK.
Alhusaini N; Department of Computer Science, School of Computer Science and Technology, University of Science and Technology of China (USTC), Hefei 230026, China.
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Źródło :
Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Sep 15; Vol. 20 (18). Date of Electronic Publication: 2020 Sep 15.
Typ publikacji :
Journal Article
MeSH Terms :
Algorithms*
Bees*
Language*
Machine Learning*
Animals ; Cluster Analysis ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
An enhanced approach to the robust discriminant analysis and class sparsity based embedding.
Autorzy :
Khoder A; University of the Basque Country UPV/EHU, San Sebastian, Spain.
Dornaika F; Henan University, Kaifeng, China; University of the Basque Country UPV/EHU, San Sebastian, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao, Spain. Electronic address: .
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Źródło :
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2021 Apr; Vol. 136, pp. 11-16. Date of Electronic Publication: 2020 Dec 30.
Typ publikacji :
Journal Article
MeSH Terms :
Algorithms*
Pattern Recognition, Automated/*trends
Supervised Machine Learning/*trends
Discriminant Analysis ; Machine Learning/trends ; Pattern Recognition, Automated/methods
Czasopismo naukowe
Tytuł :
Vulnerability of classifiers to evolutionary generated adversarial examples.
Autorzy :
Vidnerová P; The Czech Academy of Sciences, Institute of Computer Science, Pod Vodárenskou věží 271/2, 182 07 Prague 8, Czechia. Electronic address: .
Neruda R; The Czech Academy of Sciences, Institute of Computer Science, Pod Vodárenskou věží 271/2, 182 07 Prague 8, Czechia. Electronic address: .
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Źródło :
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2020 Jul; Vol. 127, pp. 168-181. Date of Electronic Publication: 2020 Apr 20.
Typ publikacji :
Journal Article
MeSH Terms :
Neural Networks, Computer*
Supervised Machine Learning*/trends
Pattern Recognition, Automated/*methods
Algorithms ; Humans ; Machine Learning/trends ; Pattern Recognition, Automated/trends
Czasopismo naukowe
Tytuł :
Supervised Machine-Learning Algorithms in Real-time Prediction of Hypotensive Events.
Autorzy :
Moghadam MC
Masoumi E
Bagherzadeh N
Ramsingh D
Kain ZN
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Źródło :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2020 Jul; Vol. 2020, pp. 5468-5471.
Typ publikacji :
Journal Article
MeSH Terms :
Hypotension*/diagnosis
Supervised Machine Learning*
Algorithms ; Humans ; Logistic Models ; Machine Learning
Czasopismo naukowe
Tytuł :
Schrödinger Spectrum Based PPG Features for the Estimation of the Arterial Blood Pressure.
Autorzy :
Li P
Laleg-Kirati TM
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Źródło :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2020 Jul; Vol. 2020, pp. 2683-2686.
Typ publikacji :
Journal Article
MeSH Terms :
Arterial Pressure*
Machine Learning*
Algorithms ; Databases, Factual ; Humans ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
ColocML: machine learning quantifies co-localization between mass spectrometry images.
Autorzy :
Ovchinnikova K; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Stuart L; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Rakhlin A; Neuromation OU, Tallinn, Estonia.
Nikolenko S; National Research Institute Higher School of Economics.; Steklov Institute of Mathematics at St. Petersburg, St. Petersburg, Russia.
Alexandrov T; Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.; Metabolomics Core Facility, European Molecular Biology Laboratory, Heidelberg, Germany.; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.
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Źródło :
Bioinformatics (Oxford, England) [Bioinformatics] 2020 May 01; Vol. 36 (10), pp. 3215-3224.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Machine Learning*
Neural Networks, Computer*
Mass Spectrometry ; Software ; Supervised Machine Learning
Czasopismo naukowe
Tytuł :
Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data.
Autorzy :
Smith AM; Unlearn.AI, Inc., San Francisco, CA, USA. .
Walsh JR; Unlearn.AI, Inc., San Francisco, CA, USA.
Long J; Computational Sciences, Worldwide Research & Development, Pfizer Inc., Cambridge, MA, USA.
Davis CB; Oncology Global Product Development, Pfizer Inc., San Diego, CA, USA.
Henstock P; Business Technology, Pfizer Inc., Cambridge, MA, USA.
Hodge MR; Inflammation and Immunology, Worldwide Research & Development, Pfizer Inc., Cambridge, MA, USA.
Maciejewski M; Inflammation and Immunology, Worldwide Research & Development, Pfizer Inc., Cambridge, MA, USA.
Mu XJ; Oncology Research & Development, Worldwide Research & Development, Pfizer Inc., San Diego, CA, USA.
Ra S; Computational Sciences, Worldwide Research & Development, Pfizer Inc., Cambridge, MA, USA.
Zhao S; Computational Sciences, Worldwide Research & Development, Pfizer Inc., Cambridge, MA, USA.
Ziemek D; Inflammation and Immunology, Worldwide Research & Development, Pfizer Pharma GmbH., Berlin, Germany.
Fisher CK; Unlearn.AI, Inc., San Francisco, CA, USA.
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Źródło :
BMC bioinformatics [BMC Bioinformatics] 2020 Mar 20; Vol. 21 (1), pp. 119. Date of Electronic Publication: 2020 Mar 20.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Gene Expression Profiling*
Machine Learning*
Phenotype*
Disease/genetics ; Humans ; Supervised Machine Learning
Czasopismo naukowe

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