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Wyświetlanie 1-20 z 447985

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Tytuł:
MLpronto: A tool for democratizing machine learning.
Autorzy:
Tjaden J; Computer Science Department, Colby College, Waterville, ME, United States of America.
Tjaden B; Department of Computer Science, Wellesley College, Wellesley, MA, United States of America.
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Źródło:
PloS one [PLoS One] 2023 Nov 30; Vol. 18 (11), pp. e0294924. Date of Electronic Publication: 2023 Nov 30 (Print Publication: 2023).
Typ publikacji:
Journal Article
MeSH Terms:
Algorithms*
Machine Learning*
Supervised Machine Learning
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data.
Autorzy:
Mo Z; Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.; School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.
Siepel A; Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.; School of Biological Sciences, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America.
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Źródło:
PLoS genetics [PLoS Genet] 2023 Nov 07; Vol. 19 (11), pp. e1011032. Date of Electronic Publication: 2023 Nov 07 (Print Publication: 2023).
Typ publikacji:
Journal Article
MeSH Terms:
Machine Learning*
Neural Networks, Computer*
Supervised Machine Learning ; Computer Simulation ; Genetics, Population
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm.
Autorzy:
Popoola AA; Georgia Institute of Technology, Atlanta, GA, USA.
Frediani JK; Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA.
Hartman TJ; Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Paynabar K; Georgia Institute of Technology, Atlanta, GA, USA. .
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2023 Sep 09; Vol. 23 (1), pp. 178. Date of Electronic Publication: 2023 Sep 09.
Typ publikacji:
Journal Article; Research Support, N.I.H., Extramural
MeSH Terms:
Algorithms*
Supervised Machine Learning*
Humans ; Random Forest ; Machine Learning ; Self Report
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
How does the model make predictions? A systematic literature review on the explainability power of machine learning in healthcare.
Autorzy:
Allgaier J; Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität Würzburg (JMU), Germany. Electronic address: .
Mulansky L; Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität Würzburg (JMU), Germany. Electronic address: .
Draelos RL; Cydoc, Durham, NC, United States of America. Electronic address: .
Pryss R; Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität Würzburg (JMU), Germany. Electronic address: .
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Źródło:
Artificial intelligence in medicine [Artif Intell Med] 2023 Sep; Vol. 143, pp. 102616. Date of Electronic Publication: 2023 Jun 24.
Typ publikacji:
Systematic Review; Journal Article
MeSH Terms:
Artificial Intelligence*
Machine Learning*
Hospitals ; Supervised Machine Learning ; Delivery of Health Care
Czasopismo naukowe
Szczegóły
Tytuł:
Identification of distinct clinical phenotypes of cardiogenic shock using machine learning consensus clustering approach.
Autorzy:
Wang L; Department of Nephrology, Changzheng Hospital, Naval Medical University, Shanghai, China.
Zhang Y; Department of Cardiothoracic Surgery, Changzheng Hospital, Naval Medical University, Shanghai, China.
Yao R; Translational Medicine Research Center, Fourth Medical Center and Medical Innovation Research Division of the Chinese PLA General Hospital, Beijing, China.; Department of Burn Surgery, Changhai Hospital, Naval Medical University, Shanghai, China.; Research Unit of key techniques for treatment of burns and combined burns and trauma injury, Chinese Academy of Medical Sciences, Shanghai, China.
Chen K; Department of Orthopedics, Changhai Hospital, Naval Medical University, Shanghai, China.
Xu Q; Department of Orthopaedics, Changzheng Hospital, Naval Medical University, Shanghai, China.
Huang R; Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Jiaotong University School of Medicine, Shanghai, China.
Mao Z; Department of Nephrology, Changzheng Hospital, Naval Medical University, Shanghai, China. .
Yu Y; Department of Cardiothoracic Surgery, Changzheng Hospital, Naval Medical University, Shanghai, China. .
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Źródło:
BMC cardiovascular disorders [BMC Cardiovasc Disord] 2023 Aug 29; Vol. 23 (1), pp. 426. Date of Electronic Publication: 2023 Aug 29.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Shock, Cardiogenic*/diagnosis
Machine Learning*
Humans ; Consensus ; Unsupervised Machine Learning ; Cluster Analysis
Czasopismo naukowe
Szczegóły
Tytuł:
Dementia prediction in the general population using clinically accessible variables: a proof-of-concept study using machine learning. The AGES-Reykjavik study.
Autorzy:
Twait EL; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.; Department of General Practice, Amsterdam UMC, location Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands.; Amsterdam Public Health, Aging & Later life and Personalized Medicine, Amsterdam, the Netherlands.; Amsterdam Neuroscience, Neurodegeneration and Mood, Anxiety, Psychosis, Stress, and Sleep, Amsterdam, the Netherlands.
Andaur Navarro CL; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.
Gudnason V; Faculty of Medicine, University of Iceland, Reykjavik, Iceland.; The Icelandic Heart Association, Kopavogur, Iceland.
Hu YH; Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA.
Launer LJ; Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA.
Geerlings MI; Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands. .; Amsterdam Public Health, Aging & Later life and Personalized Medicine, Amsterdam, the Netherlands. .; Amsterdam Neuroscience, Neurodegeneration and Mood, Anxiety, Psychosis, Stress, and Sleep, Amsterdam, the Netherlands. .; Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA. .; Department of General Practice, Amsterdam UMC, location University of Amsterdam, Meibergdreef 9, Amsterdam, the Netherlands. .
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2023 Aug 28; Vol. 23 (1), pp. 168. Date of Electronic Publication: 2023 Aug 28.
Typ publikacji:
Journal Article; Research Support, N.I.H., Intramural; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural
MeSH Terms:
Machine Learning*
Dementia*/diagnosis
Dementia*/epidemiology
Humans ; Female ; Aged ; Male ; Proof of Concept Study ; Supervised Machine Learning ; Algorithms
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach.
Autorzy:
Mousavi E; Department of Bioelectrics and Biomedical Engineering, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
Keshteli AH; Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Hezar Jerib Street, Po Box 8174673461, Isfahan, Iran.
Sehhati M; Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Hezar Jerib Street, Po Box 8174673461, Isfahan, Iran. .
Vaez A; Department of Bioinformatics, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Hezar Jerib Street, Po Box 8174673461, Isfahan, Iran.
Adibi P; Integrative Functional Gastroenterology and Hepatology Research Center, Department of Internal Medicine, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
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Źródło:
BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2023 Aug 26; Vol. 23 (1), pp. 167. Date of Electronic Publication: 2023 Aug 26.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Machine Learning*
Gastrointestinal Diseases*/diagnosis
Humans ; Cross-Sectional Studies ; Syndrome ; Unsupervised Machine Learning
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
AggBERT: Best in Class Prediction of Hexapeptide Amyloidogenesis with a Semi-Supervised ProtBERT Model.
Autorzy:
Perez R; Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Li X; Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Giannakoulias S; Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
Petersson EJ; Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States.
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Źródło:
Journal of chemical information and modeling [J Chem Inf Model] 2023 Sep 25; Vol. 63 (18), pp. 5727-5733. Date of Electronic Publication: 2023 Aug 08.
Typ publikacji:
Journal Article; Research Support, N.I.H., Extramural; Research Support, U.S. Gov't, Non-P.H.S.
MeSH Terms:
Peptides*
Machine Learning*
Amino Acid Sequence ; Amyloid ; Heuristics ; Supervised Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
Machine learning prediction and classification of behavioral selection in a canine olfactory detection program.
Autorzy:
Eyre AW; Center for Clinical and Translational Research, The Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, 43205, USA.
Zapata I; Department of Biomedical Sciences, Rocky Vista University College of Osteopathic Medicine, Parker, CO, 80134, USA.
Hare E; Dog Genetics LLC, Astoria, NY, 11102, USA.; Penn Vet Working Dog Center, Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19146, USA.
Serpell JA; Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Otto CM; Penn Vet Working Dog Center, Department of Clinical Sciences and Advanced Medicine, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, 19146, USA.
Alvarez CE; Departments of Pediatrics and Veterinary Clinical Sciences, The Ohio State University Colleges of Medicine and Veterinary Medicine, Columbus, OH, 43210, USA. .
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Źródło:
Scientific reports [Sci Rep] 2023 Aug 01; Vol. 13 (1), pp. 12489. Date of Electronic Publication: 2023 Aug 01.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Smell*
Machine Learning*
Dogs ; Animals ; Supervised Machine Learning ; Algorithms ; Mental Processes
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
NLS: An accurate and yet easy-to-interpret prediction method.
Autorzy:
Coscrato V; University College Cork, Cork, Ireland. Electronic address: .
Inácio MHA; Budapest University of Technology and Economics, Budapest, Hungary. Electronic address: .
Botari T; University of São Paulo, São Carlos - SP, Brazil. Electronic address: .
Izbicki R; Federal University of São Carlos, São Carlos - SP, Brazil. Electronic address: .
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Źródło:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2023 May; Vol. 162, pp. 117-130. Date of Electronic Publication: 2023 Mar 03.
Typ publikacji:
Journal Article
MeSH Terms:
Neural Networks, Computer*
Machine Learning*
Humans ; Algorithms ; Supervised Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
Landslide susceptibility prediction improvements based on a semi-integrated supervised machine learning model.
Autorzy:
Yang N; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.; University of Chinese Academy of Sciences, Beijing, 100049, China.
Wang R; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. .; University of Chinese Academy of Sciences, Beijing, 100049, China. .
Liu Z; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.; University of Chinese Academy of Sciences, Beijing, 100049, China.
Yao Z; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.; University of Chinese Academy of Sciences, Beijing, 100049, China.
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Źródło:
Environmental science and pollution research international [Environ Sci Pollut Res Int] 2023 Apr; Vol. 30 (17), pp. 50280-50294. Date of Electronic Publication: 2023 Feb 15.
Typ publikacji:
Journal Article
MeSH Terms:
Supervised Machine Learning*
Landslides*
Bayes Theorem ; Neural Networks, Computer ; Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
Supervised machine learning and associated algorithms: applications in orthopedic surgery.
Autorzy:
Pruneski JA; Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
Pareek A; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA. .
Kunze KN; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA.
Martin RK; Department of Orthopedic Surgery, University of Minnesota, Minneapolis, MN, USA.
Karlsson J; Orthopaedic Research Department, Göteborg University, Göteborg, Sweden.
Oeding JF; School of Medicine, Mayo Clinic Alix School of Medicine, Rochester, MN, USA.
Kiapour AM; Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
Nwachukwu BU; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA.
Williams RJ 3rd; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, 10021, USA.
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Źródło:
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA [Knee Surg Sports Traumatol Arthrosc] 2023 Apr; Vol. 31 (4), pp. 1196-1202. Date of Electronic Publication: 2022 Oct 12.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Supervised Machine Learning*
Orthopedic Procedures*
Humans ; Algorithms ; Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
Supervised learning and model analysis with compositional data.
Autorzy:
Huang S; Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.
Ailer E; Helmholtz Munich, Munich, Germany.
Kilbertus N; Helmholtz Munich, Munich, Germany.; Technical University of Munich, Munich, Germany.
Pfister N; Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark.
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Źródło:
PLoS computational biology [PLoS Comput Biol] 2023 Jun 30; Vol. 19 (6), pp. e1011240. Date of Electronic Publication: 2023 Jun 30 (Print Publication: 2023).
Typ publikacji:
Journal Article
MeSH Terms:
Algorithms*
Machine Learning*
Phylogeny ; Linear Models ; Supervised Machine Learning
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Supervised machine learning aided behavior classification in pigeons.
Autorzy:
Wittek N; Faculty of Psychology, Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany. .
Wittek K; Faculty of Mathematics, Computer Science and Natural Sciences, Department of Computer Science, RWTH Aachen University, Aachen, Germany.
Keibel C; Institute for Internet Security, Westphalian University of Applied Sciences, Gelsenkirchen, Germany.
Güntürkün O; Faculty of Psychology, Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Universitätsstraße 150, 44801, Bochum, Germany.
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Źródło:
Behavior research methods [Behav Res Methods] 2023 Jun; Vol. 55 (4), pp. 1624-1640. Date of Electronic Publication: 2022 Jun 14.
Typ publikacji:
Journal Article
MeSH Terms:
Columbidae*
Supervised Machine Learning*
Animals ; Software ; Machine Learning ; Algorithms ; Mammals
Czasopismo naukowe
Szczegóły
Tytuł:
The Impact of Supervised Learning Methods in Ultralarge High-Throughput Docking.
Autorzy:
Cavasotto CN; Computational Drug Design and Biomedical Informatics Laboratory, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET-Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.; Facultad de Ciencias Biomédicas, and Facultad de Ingeniería, Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.
Di Filippo JI; Computational Drug Design and Biomedical Informatics Laboratory, Instituto de Investigaciones en Medicina Traslacional (IIMT), CONICET-Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.; Facultad de Ciencias Biomédicas, and Facultad de Ingeniería, Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.; Austral Institute for Applied Artificial Intelligence, Universidad Austral, Av. Juan Domingo Perón 1500, B1629AHJ Pilar, Argentina.
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Źródło:
Journal of chemical information and modeling [J Chem Inf Model] 2023 Apr 24; Vol. 63 (8), pp. 2267-2280. Date of Electronic Publication: 2023 Apr 10.
Typ publikacji:
Journal Article; Review
MeSH Terms:
Drug Discovery*
Machine Learning*
Databases, Factual ; Supervised Machine Learning ; Molecular Docking Simulation ; Ligands
Czasopismo naukowe
Szczegóły
Tytuł:
Generalization of vision pre-trained models for histopathology.
Autorzy:
Sikaroudi M; Kimia Lab, University of Waterloo, Waterloo, ON, Canada.
Hosseini M; Kimia Lab, University of Waterloo, Waterloo, ON, Canada.
Gonzalez R; Kimia Lab, University of Waterloo, Waterloo, ON, Canada.; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.
Rahnamayan S; Kimia Lab, University of Waterloo, Waterloo, ON, Canada.; Engineering Department, Brock University, St. Catharines, ON, Canada.
Tizhoosh HR; Kimia Lab, University of Waterloo, Waterloo, ON, Canada. .; Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. .; Rhazes Lab, Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, USA. .
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Źródło:
Scientific reports [Sci Rep] 2023 Apr 13; Vol. 13 (1), pp. 6065. Date of Electronic Publication: 2023 Apr 13.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Neural Networks, Computer*
Machine Learning*
Humans ; Supervised Machine Learning
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
A Novel System to Increase Yield of Manufacturing Test of an RF Transceiver through Application of Machine Learning.
Autorzy:
Siddiqui A; Airbus Defence and Space, UK.
Otero P; Telecommunications Engineering School, University of Malaga, 29010 Málaga, Spain.; Institute of Oceanic Engineering Research, University of Malaga, 29010 Málaga, Spain.
Zubair M; Faculty of Engineering, Iqra University, Karachi 75850, Pakistan.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Jan 08; Vol. 23 (2). Date of Electronic Publication: 2023 Jan 08.
Typ publikacji:
Journal Article
MeSH Terms:
Machine Learning*
Commerce*
Automation ; Supervised Machine Learning ; Algorithms
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Application of Machine Learning Methods for an Analysis of E-Nose Multidimensional Signals in Wastewater Treatment.
Autorzy:
Piłat-Rożek M; Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland.
Łazuka E; Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland.
Majerek D; Faculty of Technology Fundamentals, Lublin University of Technology, 20-618 Lublin, Poland.
Szeląg B; Faculty of Environmental, Geomatic and Energy Engineering, Kielce University of Technology, 25-314 Kielce, Poland.
Duda-Saternus S; Institute of Rural Health in Lublin, 20-090 Lublin, Poland.
Łagód G; Faculty of Environmental Engineering, Lublin University of Technology, 20-618 Lublin, Poland.
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Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Jan 02; Vol. 23 (1). Date of Electronic Publication: 2023 Jan 02.
Typ publikacji:
Journal Article
MeSH Terms:
Electronic Nose*
Machine Learning*
Supervised Machine Learning ; Random Forest ; Software
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Predicting functional effects of ion channel variants using new phenotypic machine learning methods.
Autorzy:
Boßelmann CM; Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany.; Methods in Medical Informatics, Department of Computer Science, University of Tuebingen, Tuebingen, Germany.
Hedrich UBS; Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany.
Lerche H; Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany.
Pfeifer N; Methods in Medical Informatics, Department of Computer Science, University of Tuebingen, Tuebingen, Germany.; Institute for Bioinformatics and Medical Informatics, University of Tuebingen, Tuebingen, Germany.
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Źródło:
PLoS computational biology [PLoS Comput Biol] 2023 Mar 06; Vol. 19 (3), pp. e1010959. Date of Electronic Publication: 2023 Mar 06 (Print Publication: 2023).
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Machine Learning*
Ion Channels*/genetics
Humans ; Phenotype ; Genetic Association Studies ; Supervised Machine Learning
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Uncovering the complex genetic architecture of human plasma lipidome using machine learning methods.
Autorzy:
Lehtimäki M; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Mishra BH; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Del-Val C; Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain.; Instituto de Investigación Biosanitaria ibs. GRANADA, Complejo Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain.
Lyytikäinen LP; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Kähönen M; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland.
Cloninger CR; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
Raitakari OT; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Laaksonen R; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Zora Biosciences Oy, Espoo, Finland.
Zwir I; Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada, Granada, Spain.; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.; Instituto de Investigación Biosanitaria ibs. GRANADA, Complejo Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain.
Lehtimäki T; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland.; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
Mishra PP; Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. .; Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center Tampere, Tampere University, Tampere, Finland. .; Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland. .
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Źródło:
Scientific reports [Sci Rep] 2023 Feb 22; Vol. 13 (1), pp. 3078. Date of Electronic Publication: 2023 Feb 22.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Lipidomics*
Machine Learning*
Humans ; Genotype ; Phenotype ; Unsupervised Machine Learning ; Polymorphism, Single Nucleotide
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Wyświetlanie 1-20 z 447985

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