Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Ukraiński (UK)
Przejdź do strony domowej biblioteki Uniwersytet Ekonomiczny we Wrocławiu Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaUniwersytet Ekonomiczny we Wrocławiu

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

  Lista filtrów
Wyrównaj
Wyświetlanie 1-20 z 804277

Starter badań:

Tytuł:
Evaluation metrics and statistical tests for machine learning.
Autorzy:
Rainio O; Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland. .
Teuho J; Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland.
Klén R; Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland.
Pokaż więcej
Źródło:
Scientific reports [Sci Rep] 2024 Mar 13; Vol. 14 (1), pp. 6086. Date of Electronic Publication: 2024 Mar 13.
Typ publikacji:
Journal Article
MeSH Terms:
Image Processing, Computer-Assisted*/methods
Machine Learning*
Neural Networks, Computer ; Supervised Machine Learning ; Positron-Emission Tomography
Czasopismo naukowe
Szczegóły
Tytuł:
Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification.
Autorzy:
Tutsoy O; Adana Alparslan Turkes Science and Technology University, Adana, Turkey. .
Koç GG; Adana Alparslan Turkes Science and Technology University, Adana, Turkey.
Pokaż więcej
Źródło:
BMC bioinformatics [BMC Bioinformatics] 2024 Mar 08; Vol. 25 (1), pp. 103. Date of Electronic Publication: 2024 Mar 08.
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:
Segmenting mechanically heterogeneous domains via unsupervised learning.
Autorzy:
Nguyen Q; Department of Mechanical Engineering, Boston University, Boston, MA, 02215, USA.
Lejeune E; Department of Mechanical Engineering, Boston University, Boston, MA, 02215, USA. .
Pokaż więcej
Źródło:
Biomechanics and modeling in mechanobiology [Biomech Model Mechanobiol] 2024 Feb; Vol. 23 (1), pp. 349-372. Date of Electronic Publication: 2024 Jan 13.
Typ publikacji:
Journal Article
MeSH Terms:
Unsupervised Machine Learning*
Robotics*/methods
Machine Learning ; Computer Simulation ; Biomechanical Phenomena
Czasopismo naukowe
Szczegóły
Tytuł:
An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.
Autorzy:
Gallegos M; Department of Analytical and Physical Chemistry, University of Oviedo, Oviedo E-33006, Spain.
Isamura BK; Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
Popelier PLA; Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, U.K.
Martín Pendás Á; Department of Analytical and Physical Chemistry, University of Oviedo, Oviedo E-33006, Spain.
Pokaż więcej
Źródło:
Journal of chemical information and modeling [J Chem Inf Model] 2024 Apr 22; Vol. 64 (8), pp. 3059-3079. Date of Electronic Publication: 2024 Mar 18.
Typ publikacji:
Journal Article
MeSH Terms:
Unsupervised Machine Learning*
Neural Networks, Computer*
Reproducibility of Results ; Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
The impacts of active and self-supervised learning on efficient annotation of single-cell expression data.
Autorzy:
Geuenich MJ; Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, M5G 1×5, Canada. .; Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada. .
Gong DW; Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, M5G 1×5, Canada.
Campbell KR; Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, M5G 1×5, Canada. .; Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada. .; Department of Statistical Sciences, University of Toronto, Toronto, ON, M5S 3G3, Canada. .; Department of Computer Science, University of Toronto, Toronto, ON, M5T 3A1, Canada. .; Ontario Institute of Cancer Research, Toronto, ON, M5G 1M1, Canada. .; Vector Institute, Toronto, ON, M5G 1M1, Canada. .
Pokaż więcej
Źródło:
Nature communications [Nat Commun] 2024 Feb 03; Vol. 15 (1), pp. 1014. Date of Electronic Publication: 2024 Feb 03.
Typ publikacji:
Journal Article
MeSH Terms:
Machine Learning*
Algorithms*
Technology ; Awareness ; Supervised Machine Learning ; Single-Cell Analysis
Czasopismo naukowe
Szczegóły
Tytuł:
Semi-supervised Learning for Generalizable Intracranial Hemorrhage Detection and Segmentation.
Autorzy:
Lin E; From the Department of Radiology & Biomedical Imaging, University of California San Francisco, 185 Berry St, San Francisco CA 94107.
Yuh EL; From the Department of Radiology & Biomedical Imaging, University of California San Francisco, 185 Berry St, San Francisco CA 94107.
Pokaż więcej
Źródło:
Radiology. Artificial intelligence [Radiol Artif Intell] 2024 May; Vol. 6 (3), pp. e230077.
Typ publikacji:
Journal Article
MeSH Terms:
Intracranial Hemorrhages*/diagnosis
Supervised Machine Learning*
Humans ; Retrospective Studies ; Machine Learning ; Benchmarking
Czasopismo naukowe
Szczegóły
Tytuł:
Distribution-free Bayesian regularized learning framework for semi-supervised learning.
Autorzy:
Ma J; School of Mathematics and Information Sciences, North Minzu University, Yinchuan Ningxia 750021, PR China. Electronic address: jun_.
Yu G; School of Mathematics and Information Sciences, North Minzu University, Yinchuan Ningxia 750021, PR China. Electronic address: .
Pokaż więcej
Źródło:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2024 Jun; Vol. 174, pp. 106262. Date of Electronic Publication: 2024 Mar 20.
Typ publikacji:
Journal Article
MeSH Terms:
Algorithms*
Supervised Machine Learning*
Bayes Theorem ; Reproducibility of Results ; Machine Learning
Czasopismo naukowe
Szczegóły
Tytuł:
Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.
Autorzy:
Lemmon J; Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON M5G1X8, Canada.
Guo LL; Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON M5G1X8, Canada.
Steinberg E; Stanford Center for Biomedical Informatics Research, Stanford University, Palo Alto, CA 94305, United States.
Morse KE; Division of Pediatric Hospital Medicine, Department of Pediatrics, Stanford University, Palo Alto, CA 94304, United States.
Fleming SL; Stanford Center for Biomedical Informatics Research, Stanford University, Palo Alto, CA 94305, United States.
Aftandilian C; Division of Hematology/Oncology, Department of Pediatrics, Stanford University, Palo Alto, CA 94304, United States.
Pfohl SR; Google Research, Mountain View, CA 94043, United States.
Posada JD; Universidad del Norte, Barranquilla 081007, Colombia.
Shah N; Stanford Center for Biomedical Informatics Research, Stanford University, Palo Alto, CA 94305, United States.
Fries J; Stanford Center for Biomedical Informatics Research, Stanford University, Palo Alto, CA 94305, United States.
Sung L; Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON M5G1X8, Canada.; Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, ON M5G1X8, Canada.
Pokaż więcej
Źródło:
Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2023 Nov 17; Vol. 30 (12), pp. 2004-2011.
Typ publikacji:
Journal Article
MeSH Terms:
Inpatients*
Machine Learning*
Humans ; Adult ; Child ; Retrospective Studies ; Supervised Machine Learning ; Electronic Health Records
Czasopismo naukowe
Szczegóły
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.
Pokaż więcej
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.
Pokaż więcej
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. .
Pokaż więcej
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: .
Pokaż więcej
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. .
Pokaż więcej
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. .
Pokaż więcej
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.
Pokaż więcej
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:
Segment-Based Unsupervised Learning Method in Sensor-Based Human Activity Recognition.
Autorzy:
Takenaka K; Graduate School of Engineering, University of Fukui, Fukui 910-8507, Japan.
Kondo K; Graduate School of Engineering, University of Fukui, Fukui 910-8507, Japan.
Hasegawa T; Graduate School of Engineering, University of Fukui, Fukui 910-8507, Japan.
Pokaż więcej
Źródło:
Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Oct 13; Vol. 23 (20). Date of Electronic Publication: 2023 Oct 13.
Typ publikacji:
Journal Article
MeSH Terms:
Unsupervised Machine Learning*
Labor, Obstetric*
Female ; Pregnancy ; Humans ; Human Activities ; Machine Learning ; Recognition, Psychology
Czasopismo naukowe
Pełny tekst  Link otwiera się w nowym oknie Pełny tekstSzczegóły
Tytuł:
Insight Extraction From E-Health Bookings by Means of Hypergraph and Machine Learning.
Autorzy:
Schiano di Cola V
Chiaro D
Prezioso E
Izzo S
Giampaolo F
Pokaż więcej
Źródło:
IEEE journal of biomedical and health informatics [IEEE J Biomed Health Inform] 2023 Oct; Vol. 27 (10), pp. 4649-4659. Date of Electronic Publication: 2023 Oct 05.
Typ publikacji:
Journal Article
MeSH Terms:
Machine Learning*
Telemedicine*
Humans ; Supervised Machine Learning ; Databases, Factual ; Probability ; Algorithms
Czasopismo naukowe
Szczegóły
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.
Pokaż więcej
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:
High-Order Correlation-Guided Slide-Level Histology Retrieval With Self-Supervised Hashing.
Autorzy:
Li S
Zhao Y
Zhang J
Yu T
Zhang J
Gao Y
Pokaż więcej
Źródło:
IEEE transactions on pattern analysis and machine intelligence [IEEE Trans Pattern Anal Mach Intell] 2023 Sep; Vol. 45 (9), pp. 11008-11023. Date of Electronic Publication: 2023 Aug 07.
Typ publikacji:
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms:
Histology*
Pattern Recognition, Automated*/methods
Supervised Machine Learning*
Algorithms ; Cluster Analysis ; Datasets as Topic ; Image Interpretation, Computer-Assisted/methods ; Neoplasms/classification ; Neoplasms/diagnosis ; Neoplasms/pathology ; Pathology/methods ; Unsupervised Machine Learning ; Humans
Czasopismo naukowe
Szczegóły
Wyświetlanie 1-20 z 804277

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies