Výsledky vyhledávání - "Machine Learning [MeSH]"
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Zdroj: Bioinformatics. 41(9)
Témata: 31 Biological Sciences (for-2020), 3106 Industrial Biotechnology (for-2020), Genetics (rcdc), Biotechnology (rcdc), Bioengineering (rcdc), Escherichia coli (mesh), Metabolic Engineering (mesh), Software (mesh), Synthetic Biology (mesh), Pseudomonas putida (mesh), Machine Learning (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Metabolic Networks and Pathways (mesh), Pseudomonas putida (mesh), Escherichia coli (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Software (mesh), Metabolic Networks and Pathways (mesh), Synthetic Biology (mesh), Metabolic Engineering (mesh), Machine Learning (mesh), Escherichia coli (mesh), Metabolic Engineering (mesh), Software (mesh), Synthetic Biology (mesh), Pseudomonas putida (mesh), Machine Learning (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Metabolic Networks and Pathways (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)
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2
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Zdroj: Journal of Clinical Investigation. 135(17)
Témata: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 32 Biomedical and Clinical Sciences (for-2020), Emerging Infectious Diseases (rcdc), Infectious Diseases (rcdc), Genetics (rcdc), Rare Diseases (rcdc), Biodefense (rcdc), 2.1 Biological and endogenous factors (hrcs-rac), Infection (hrcs-hc), 3 Good Health and Well Being (sdg), Adult (mesh), Female (mesh), Humans (mesh), Male (mesh), Middle Aged (mesh), Leprosy (mesh), Machine Learning (mesh), Mycobacterium leprae (mesh), Skin (mesh), Th1 Cells (mesh), Th17 Cells (mesh), Th1 Cells (mesh), Skin (mesh), Humans (mesh), Mycobacterium leprae (mesh), Leprosy (mesh), Adult (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Th17 Cells (mesh), Machine Learning (mesh), Adaptive immunity, Bacterial infections, Immunology, Infectious disease, Innate immunity, Adult (mesh), Female (mesh), Humans (mesh), Male (mesh), Middle Aged (mesh), Leprosy (mesh), Machine Learning (mesh), Mycobacterium leprae (mesh), Skin (mesh), Th1 Cells (mesh), Th17 Cells (mesh), 11 Medical and Health Sciences (for), Immunology (science-metrix), 31 Biological sciences (for-2020), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020)
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Zdroj: Alzheimer's & Dementia. 21(8)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 5202 Biological Psychology (for-2020), 3202 Clinical Sciences (for-2020), 3209 Neurosciences (for-2020), 52 Psychology (for-2020), Aging (rcdc), Machine Learning and Artificial Intelligence (rcdc), Dementia (rcdc), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc), Neurosciences (rcdc), Acquired Cognitive Impairment (rcdc), Behavioral and Social Science (rcdc), Neurodegenerative (rcdc), Prevention (rcdc), Alzheimer's Disease (rcdc), Brain Disorders (rcdc), Neurological (hrcs-hc), 3 Good Health and Well Being (sdg), 4 Quality Education (sdg), Aged (mesh), Aged, 80 and over (mesh), Female (mesh), Humans (mesh), Male (mesh), Middle Aged (mesh), Aging (mesh), Black or African American (mesh), Cognitive Dysfunction (mesh), Cohort Studies (mesh), Cross-Sectional Studies (mesh), Machine Learning (mesh), Memory, Episodic (mesh), Neuropsychological Tests (mesh), Risk Factors (mesh), Surveys and Questionnaires (mesh), United States (mesh), Racial Groups (mesh), episodic memory, life exposure factors, regression tree models, SHAP values, XGBoost, Humans (mesh), Risk Factors (mesh), Cohort Studies (mesh), Cross-Sectional Studies (mesh), Neuropsychological Tests (mesh), Aging (mesh), Aged (mesh), Aged, 80 and over (mesh), Middle Aged (mesh), United States (mesh), Female (mesh), Male (mesh), Memory, Episodic (mesh), Machine Learning (mesh), Surveys and Questionnaires (mesh), Cognitive Dysfunction (mesh), Racial Groups (mesh), Black or African American (mesh), SHAP values, XGBoost, episodic memory, life exposure factors, regression tree models, Aged (mesh), Aged, 80 and over (mesh), Female (mesh), Humans (mesh), Male (mesh), Middle Aged (mesh), Aging (mesh), Black or African American (mesh), Cognitive Dysfunction (mesh), Cohort Studies (mesh), Cross-Sectional Studies (mesh), Machine Learning (mesh), Memory, Episodic (mesh), Neuropsychological Tests (mesh), Risk Factors (mesh), Surveys and Questionnaires (mesh), United States (mesh), Racial Groups (mesh), 1103 Clinical Sciences (for), 1109 Neurosciences (for), Geriatrics (science-metrix), 3202 Clinical sciences (for-2020), 3209 Neurosciences (for-2020), 5202 Biological psychology (for-2020)
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Zdroj: Nature. 643(8072)
Témata: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 32 Biomedical and Clinical Sciences (for-2020), Genetics (rcdc), Machine Learning and Artificial Intelligence (rcdc), 1.1 Normal biological development and functioning (hrcs-rac), Animals (mesh), Female (mesh), Humans (mesh), Male (mesh), Mice (mesh), Alleles (mesh), Base Pairing (mesh), Brain (mesh), Enhancer Elements, Genetic (mesh), Machine Learning (mesh), Mice, Transgenic (mesh), Mutagenesis (mesh), Mutation (mesh), Nucleotide Motifs (mesh), Brain (mesh), Animals (mesh), Mice, Transgenic (mesh), Humans (mesh), Mice (mesh), Mutagenesis (mesh), Base Pairing (mesh), Mutation (mesh), Alleles (mesh), Female (mesh), Male (mesh), Enhancer Elements, Genetic (mesh), Nucleotide Motifs (mesh), Machine Learning (mesh), Animals (mesh), Female (mesh), Humans (mesh), Male (mesh), Mice (mesh), Alleles (mesh), Base Pairing (mesh), Brain (mesh), Enhancer Elements, Genetic (mesh), Machine Learning (mesh), Mice, Transgenic (mesh), Mutagenesis (mesh), Mutation (mesh), Nucleotide Motifs (mesh), General Science & Technology (science-metrix)
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Zdroj: Nature Communications. 16(1)
Témata: 4613 Theory Of Computation (for-2020), 3404 Medicinal and Biomolecular Chemistry (for-2020), 34 Chemical Sciences (for-2020), 46 Information and Computing Sciences (for-2020), 4611 Machine Learning (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Bioengineering (rcdc), Biotechnology (rcdc), Generic health relevance (hrcs-hc), Humans (mesh), Receptors, G-Protein-Coupled (mesh), Drug Discovery (mesh), Neural Networks, Computer (mesh), Machine Learning (mesh), Humans (mesh), Receptors, G-Protein-Coupled (mesh), Drug Discovery (mesh), Machine Learning (mesh), Neural Networks, Computer (mesh), Humans (mesh), Receptors, G-Protein-Coupled (mesh), Drug Discovery (mesh), Neural Networks, Computer (mesh), Machine Learning (mesh)
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Zdroj: Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology. 17(4)
Témata: 3206 Medical Biotechnology (for-2020), 32 Biomedical and Clinical Sciences (for-2020), Data Science (rcdc), Biotechnology (rcdc), Bioengineering (rcdc), Cancer (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Nanotechnology (rcdc), Machine Learning and Artificial Intelligence (rcdc), 5.1 Pharmaceuticals (hrcs-rac), Generic health relevance (hrcs-hc), 3 Good Health and Well Being (sdg), Nanomedicine (mesh), Humans (mesh), Machine Learning (mesh), Artificial Intelligence (mesh), Animals (mesh), Nanoparticles (mesh), artificial intelligence, drug delivery, machine learning, nanomedicine, pharmacokinetics, Animals (mesh), Humans (mesh), Artificial Intelligence (mesh), Nanomedicine (mesh), Nanoparticles (mesh), Machine Learning (mesh), artificial intelligence, drug delivery, machine learning, nanomedicine, pharmacokinetics, Nanomedicine (mesh), Humans (mesh), Machine Learning (mesh), Artificial Intelligence (mesh), Animals (mesh), Nanoparticles (mesh), 0304 Medicinal and Biomolecular Chemistry (for), 0903 Biomedical Engineering (for), 1007 Nanotechnology (for), Nanoscience & Nanotechnology (science-metrix), 3206 Medical biotechnology (for-2020), 3404 Medicinal and biomolecular chemistry (for-2020), 4018 Nanotechnology (for-2020)
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Zdroj: International Angiology. 44(3)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), Stroke (rcdc), Prevention (rcdc), Machine Learning and Artificial Intelligence (rcdc), Neurosciences (rcdc), Cerebrovascular (rcdc), Brain Disorders (rcdc), Cardiovascular (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), Carotid Stenosis (mesh), Asymptomatic Diseases (mesh), Stroke (mesh), Risk Assessment (mesh), Risk Factors (mesh), Machine Learning (mesh), Artificial Intelligence (mesh), Carotid stenosis, Stroke, Transient ischemic attack, Humans (mesh), Carotid Stenosis (mesh), Risk Assessment (mesh), Risk Factors (mesh), Artificial Intelligence (mesh), Stroke (mesh), Asymptomatic Diseases (mesh), Machine Learning (mesh), Humans (mesh), Carotid Stenosis (mesh), Asymptomatic Diseases (mesh), Stroke (mesh), Risk Assessment (mesh), Risk Factors (mesh), Machine Learning (mesh), Artificial Intelligence (mesh), 1103 Clinical Sciences (for), Cardiovascular System & Hematology (science-metrix), 3201 Cardiovascular medicine and haematology (for-2020), 3202 Clinical sciences (for-2020)
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Zdroj: Bioinformatics. 41(4)
Témata: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 4601 Applied Computing (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Microscopy, Fluorescence (mesh), Software (mesh), Image Processing, Computer-Assisted (mesh), Machine Learning (mesh), Humans (mesh), Humans (mesh), Microscopy, Fluorescence (mesh), Image Processing, Computer-Assisted (mesh), Software (mesh), Machine Learning (mesh), Microscopy, Fluorescence (mesh), Software (mesh), Image Processing, Computer-Assisted (mesh), Machine Learning (mesh), Humans (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)
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Zdroj: Inflammatory Bowel Diseases. 31(3)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), Inflammatory Bowel Disease (rcdc), Autoimmune Disease (rcdc), Cancer (rcdc), Digestive Diseases (rcdc), Machine Learning and Artificial Intelligence (rcdc), Clinical Research (rcdc), Humans (mesh), Colonoscopy (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), Algorithms (mesh), Colitis, Ulcerative (mesh), Severity of Illness Index (mesh), Middle Aged (mesh), Adult (mesh), ulcerative colitis, endoscopic disease activity scores, natural language processing, healthcare applied AI, Humans (mesh), Colitis, Ulcerative (mesh), Colonoscopy (mesh), Severity of Illness Index (mesh), Algorithms (mesh), Adult (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), endoscopic disease activity scores, healthcare applied AI, natural language processing, ulcerative colitis, Humans (mesh), Colonoscopy (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), Algorithms (mesh), Colitis, Ulcerative (mesh), Severity of Illness Index (mesh), Middle Aged (mesh), Adult (mesh), 1103 Clinical Sciences (for), Gastroenterology & Hepatology (science-metrix), 3202 Clinical sciences (for-2020)
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Zdroj: The Journal of Infectious Diseases. 231(2)
Témata: 3207 Medical Microbiology (for-2020), 32 Biomedical and Clinical Sciences (for-2020), 3204 Immunology (for-2020), Sexually Transmitted Infections (rcdc), HIV/AIDS (rcdc), Minority Health (rcdc), Machine Learning and Artificial Intelligence (rcdc), Infectious Diseases (rcdc), Clinical Research (rcdc), Infection (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), HIV Infections (mesh), Viral Load (mesh), Viremia (mesh), Anti-HIV Agents (mesh), Machine Learning (mesh), Models, Theoretical (mesh), Male (mesh), HIV-1 (mesh), Female (mesh), Adult (mesh), Treatment Outcome (mesh), Withholding Treatment (mesh), Treatment Interruption (mesh), HIV, sustained virologic response, posttreatment control, analytical treatment interruption, viral rebound, Humans (mesh), HIV-1 (mesh), Viremia (mesh), HIV Infections (mesh), Anti-HIV Agents (mesh), Treatment Outcome (mesh), Withholding Treatment (mesh), Viral Load (mesh), Models, Theoretical (mesh), Adult (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), Treatment Interruption (mesh), HIV, analytical treatment interruption, posttreatment control, sustained virologic response, viral rebound, Humans (mesh), HIV Infections (mesh), Viral Load (mesh), Viremia (mesh), Anti-HIV Agents (mesh), Machine Learning (mesh), Models, Theoretical (mesh), Male (mesh), HIV-1 (mesh), Female (mesh), Adult (mesh), Treatment Outcome (mesh), Withholding Treatment (mesh), Treatment Interruption (mesh), 06 Biological Sciences (for), 11 Medical and Health Sciences (for), Microbiology (science-metrix), 31 Biological sciences (for-2020), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020)
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Zdroj: BMJ Open. 15(2)
Témata: 4206 Public Health (for-2020), 42 Health Sciences (for-2020), Machine Learning and Artificial Intelligence (rcdc), Diabetes (rcdc), Nutrition (rcdc), Data Science (rcdc), Clinical Research (rcdc), Behavioral and Social Science (rcdc), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Metabolic and endocrine (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), Cross-Sectional Studies (mesh), Diabetes Mellitus, Type 2 (mesh), Artificial Intelligence (mesh), Male (mesh), Female (mesh), Middle Aged (mesh), Adult (mesh), Research Design (mesh), Aged (mesh), Machine Learning (mesh), Diabetic nephropathy & vascular disease, Diabetic retinopathy, Diabetic neuropathy, Diabetes Mellitus, Type 2, EPIDEMIOLOGY, AI-READI Consortium, Humans (mesh), Diabetes Mellitus, Type 2 (mesh), Cross-Sectional Studies (mesh), Research Design (mesh), Artificial Intelligence (mesh), Adult (mesh), Aged (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), Diabetes Mellitus, Type 2, Diabetic nephropathy & vascular disease, Diabetic neuropathy, Diabetic retinopathy, EPIDEMIOLOGY, Humans (mesh), Cross-Sectional Studies (mesh), Diabetes Mellitus, Type 2 (mesh), Artificial Intelligence (mesh), Male (mesh), Female (mesh), Middle Aged (mesh), Adult (mesh), Research Design (mesh), Aged (mesh), Machine Learning (mesh), 1103 Clinical Sciences (for), 1117 Public Health and Health Services (for), 1199 Other Medical and Health Sciences (for), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020), 52 Psychology (for-2020)
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Zdroj: Journal of Magnetic Resonance Imaging. 61(2)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3211 Oncology and Carcinogenesis (for-2020), Machine Learning and Artificial Intelligence (rcdc), Women's Health (rcdc), Breast Cancer (rcdc), Clinical Research (rcdc), Cancer (rcdc), Biomedical Imaging (rcdc), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Humans (mesh), Female (mesh), Breast Neoplasms (mesh), Machine Learning (mesh), Magnetic Resonance Imaging (mesh), Retrospective Studies (mesh), Middle Aged (mesh), Receptor, ErbB-2 (mesh), Carcinoma, Ductal, Breast (mesh), Adult (mesh), Aged (mesh), Breast (mesh), Image Interpretation, Computer-Assisted (mesh), Reproducibility of Results (mesh), Algorithms (mesh), ROC Curve (mesh), breast cancer, HER2 positive, HER2 low, magnetic resonance imaging, Breast (mesh), Humans (mesh), Carcinoma, Ductal, Breast (mesh), Breast Neoplasms (mesh), Receptor, erbB-2 (mesh), Image Interpretation, Computer-Assisted (mesh), Magnetic Resonance Imaging (mesh), Retrospective Studies (mesh), Reproducibility of Results (mesh), ROC Curve (mesh), Algorithms (mesh), Adult (mesh), Aged (mesh), Middle Aged (mesh), Female (mesh), Machine Learning (mesh), HER2 low, HER2 positive, breast cancer, magnetic resonance imaging, Humans (mesh), Female (mesh), Breast Neoplasms (mesh), Machine Learning (mesh), Magnetic Resonance Imaging (mesh), Retrospective Studies (mesh), Middle Aged (mesh), Receptor, ErbB-2 (mesh), Carcinoma, Ductal, Breast (mesh), Adult (mesh), Aged (mesh), Breast (mesh), Image Interpretation, Computer-Assisted (mesh), Reproducibility of Results (mesh), Algorithms (mesh), ROC Curve (mesh), 02 Physical Sciences (for), 09 Engineering (for), 11 Medical and Health Sciences (for), Nuclear Medicine & Medical Imaging (science-metrix), 3202 Clinical sciences (for-2020)
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Zdroj: Alzheimer's & Dementia. 21(2)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 5202 Biological Psychology (for-2020), 3202 Clinical Sciences (for-2020), 3209 Neurosciences (for-2020), 52 Psychology (for-2020), Acquired Cognitive Impairment (rcdc), Alzheimer's Disease (rcdc), Neurodegenerative (rcdc), Brain Disorders (rcdc), Dementia (rcdc), Neurosciences (rcdc), Aging (rcdc), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), 2.1 Biological and endogenous factors (hrcs-rac), 4.2 Evaluation of markers and technologies (hrcs-rac), Neurological (hrcs-hc), Humans (mesh), Alzheimer Disease (mesh), Biomarkers (mesh), Disease Progression (mesh), Cluster Analysis (mesh), Unsupervised Machine Learning (mesh), Neuroimaging (mesh), Female (mesh), Male (mesh), Aged (mesh), Brain (mesh), Amyloid beta-Peptides (mesh), Alzheimer's disease, amyloid cascade hypothesis, biomarker progression, cluster analysis, dementia, heterogeneity, K-means clustering, precision medicine, trajectories, unsupervised learning, Alzheimer's Disease Neuroimaging Initiative, Brain (mesh), Humans (mesh), Alzheimer Disease (mesh), Disease Progression (mesh), Cluster Analysis (mesh), Aged (mesh), Female (mesh), Male (mesh), Amyloid beta-Peptides (mesh), Neuroimaging (mesh), Biomarkers (mesh), Unsupervised Machine Learning (mesh), Alzheimer's disease, K‐means clustering, amyloid cascade hypothesis, biomarker progression, cluster analysis, dementia, heterogeneity, precision medicine, trajectories, unsupervised learning, Humans (mesh), Alzheimer Disease (mesh), Biomarkers (mesh), Disease Progression (mesh), Cluster Analysis (mesh), Unsupervised Machine Learning (mesh), Neuroimaging (mesh), Female (mesh), Male (mesh), Aged (mesh), Brain (mesh), Amyloid beta-Peptides (mesh), 1103 Clinical Sciences (for), 1109 Neurosciences (for), Geriatrics (science-metrix), 3202 Clinical sciences (for-2020), 3209 Neurosciences (for-2020), 5202 Biological psychology (for-2020)
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Zdroj: Alzheimer's & Dementia. 21(2)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), Neurosciences (rcdc), Aging (rcdc), Alzheimer's Disease (rcdc), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc), Dementia (rcdc), Machine Learning and Artificial Intelligence (rcdc), Biomedical Imaging (rcdc), Clinical Research (rcdc), Acquired Cognitive Impairment (rcdc), Brain Disorders (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Neurodegenerative (rcdc), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), 4.2 Evaluation of markers and technologies (hrcs-rac), Neurological (hrcs-hc), Humans (mesh), Machine Learning (mesh), tau Proteins (mesh), Alzheimer Disease (mesh), Positron-Emission Tomography (mesh), Magnetic Resonance Imaging (mesh), Male (mesh), Female (mesh), Aged (mesh), Biomarkers (mesh), Brain (mesh), Brain (mesh), Humans (mesh), Alzheimer Disease (mesh), tau Proteins (mesh), Positron-Emission Tomography (mesh), Magnetic Resonance Imaging (mesh), Aged (mesh), Female (mesh), Male (mesh), Biomarkers (mesh), Machine Learning (mesh), Humans (mesh), Machine Learning (mesh), tau Proteins (mesh), Alzheimer Disease (mesh), Positron-Emission Tomography (mesh), Magnetic Resonance Imaging (mesh), Male (mesh), Female (mesh), Aged (mesh), Biomarkers (mesh), Brain (mesh), 1103 Clinical Sciences (for), 1109 Neurosciences (for), Geriatrics (science-metrix), 3202 Clinical sciences (for-2020), 3209 Neurosciences (for-2020), 5202 Biological psychology (for-2020)
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Zdroj: Journal of Neuropathology & Experimental Neurology. 84(2)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3209 Neurosciences (for-2020), 3202 Clinical Sciences (for-2020), Machine Learning and Artificial Intelligence (rcdc), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) (rcdc), Neurosciences (rcdc), Dementia (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Brain Disorders (rcdc), Cerebrovascular (rcdc), Aging (rcdc), Bioengineering (rcdc), Acquired Cognitive Impairment (rcdc), Neurodegenerative (rcdc), 4.2 Evaluation of markers and technologies (hrcs-rac), Neurological (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), Machine Learning (mesh), Male (mesh), Aged (mesh), Female (mesh), Brain (mesh), Cerebral Hemorrhage (mesh), Aged, 80 and over (mesh), Hematoxylin (mesh), Eosine Yellowish-(YS) (mesh), Brain Infarction (mesh), Middle Aged (mesh), Staining and Labeling (mesh), deep learning, digital pathology, histology, infarcts, vascular dementia, Brain (mesh), Humans (mesh), Brain Infarction (mesh), Cerebral Hemorrhage (mesh), Hematoxylin (mesh), Eosine Yellowish-(YS) (mesh), Staining and Labeling (mesh), Aged (mesh), Aged, 80 and over (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Machine Learning (mesh), deep learning, digital pathology, histology, infarcts, vascular dementia, Humans (mesh), Machine Learning (mesh), Male (mesh), Aged (mesh), Female (mesh), Brain (mesh), Cerebral Hemorrhage (mesh), Aged, 80 and over (mesh), Hematoxylin (mesh), Eosine Yellowish-(YS) (mesh), Brain Infarction (mesh), Middle Aged (mesh), Staining and Labeling (mesh), 1103 Clinical Sciences (for), 1109 Neurosciences (for), Neurology & Neurosurgery (science-metrix), 3202 Clinical sciences (for-2020), 3209 Neurosciences (for-2020)
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Zdroj: Scientific Reports. 15(1)
Témata: 4605 Data Management and Data Science (for-2020), 46 Information and Computing Sciences (for-2020), Machine Learning and Artificial Intelligence (rcdc), Cancer (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Prevention (rcdc), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), Cancer (hrcs-hc), Algorithms (mesh), Humans (mesh), Neoplasms (mesh), Machine Learning (mesh), Medical dataset, Feature selection, Al-Biruni Earth radius optimization algorithm, Cancer treatment, Humans (mesh), Neoplasms (mesh), Algorithms (mesh), Machine Learning (mesh), Al-Biruni Earth radius optimization algorithm, Cancer treatment, Feature selection, Medical dataset, Algorithms (mesh), Humans (mesh), Neoplasms (mesh), Machine Learning (mesh)
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Zdroj: Ophthalmology Glaucoma. 8(1)
Témata: 32 Biomedical and Clinical Sciences (for-2020), 3212 Ophthalmology and Optometry (for-2020), Clinical Research (rcdc), Machine Learning and Artificial Intelligence (rcdc), Neurosciences (rcdc), Aging (rcdc), Neurodegenerative (rcdc), Eye Disease and Disorders of Vision (rcdc), Data Science (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Generic health relevance (hrcs-hc), Eye (hrcs-hc), Humans (mesh), Glaucoma (mesh), Artificial Intelligence (mesh), Deep Learning (mesh), Machine Learning (mesh), Federated Learning (mesh), Humans (mesh), Glaucoma (mesh), Artificial Intelligence (mesh), Machine Learning (mesh), Deep Learning (mesh), Federated Learning (mesh), Artificial intelligence, Federated learning, Glaucoma, Privacy, Humans (mesh), Glaucoma (mesh), Artificial Intelligence (mesh), Deep Learning (mesh), Machine Learning (mesh), Federated Learning (mesh)
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Zdroj: Microbiome. 13(1)
Témata: 3107 Microbiology (for-2020), 31 Biological Sciences (for-2020), Machine Learning and Artificial Intelligence (rcdc), Obesity (rcdc), Chronic Liver Disease and Cirrhosis (rcdc), Liver Disease (rcdc), Nutrition (rcdc), Genetics (rcdc), Hepatitis (rcdc), Microbiome (rcdc), Digestive Diseases (rcdc), Prevention (rcdc), 2.1 Biological and endogenous factors (hrcs-rac), Metabolic and endocrine (hrcs-hc), Oral and gastrointestinal (hrcs-hc), Cardiovascular (hrcs-hc), Non-alcoholic Fatty Liver Disease (mesh), Humans (mesh), Gastrointestinal Microbiome (mesh), Male (mesh), Metagenomics (mesh), Female (mesh), Bacteria (mesh), Middle Aged (mesh), Adult (mesh), Machine Learning (mesh), Obesity (mesh), NAFLD, Gut microbiota, Metabolic diseases, Machine learning, Network analysis, Metabolomics, Microbial consortia, Humans (mesh), Bacteria (mesh), Obesity (mesh), Adult (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Metagenomics (mesh), Non-alcoholic Fatty Liver Disease (mesh), Machine Learning (mesh), Gastrointestinal Microbiome (mesh), Gut microbiota, Machine learning, Metabolic diseases, Metabolomics, Microbial consortia, NAFLD, Network analysis, Non-alcoholic Fatty Liver Disease (mesh), Humans (mesh), Gastrointestinal Microbiome (mesh), Male (mesh), Metagenomics (mesh), Female (mesh), Bacteria (mesh), Middle Aged (mesh), Adult (mesh), Machine Learning (mesh), Obesity (mesh), 0602 Ecology (for), 0605 Microbiology (for), 1108 Medical Microbiology (for), 3104 Evolutionary biology (for-2020), 3107 Microbiology (for-2020)
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Zdroj: PLOS Computational Biology. 21(2)
Témata: 31 Biological Sciences (for-2020), 3105 Genetics (for-2020), Human Genome (rcdc), Social Determinants of Health (rcdc), Genetics (rcdc), Generic health relevance (hrcs-hc), DNA Methylation (mesh), Humans (mesh), Epigenesis, Genetic (mesh), CpG Islands (mesh), Phenotype (mesh), Computational Biology (mesh), Adult (mesh), Epigenomics (mesh), Child (mesh), Machine Learning (mesh), Principal Component Analysis (mesh), Aging (mesh), Male (mesh), Humans (mesh), Computational Biology (mesh), DNA Methylation (mesh), Epigenesis, Genetic (mesh), CpG Islands (mesh), Aging (mesh), Phenotype (mesh), Principal Component Analysis (mesh), Adult (mesh), Child (mesh), Male (mesh), Epigenomics (mesh), Machine Learning (mesh), DNA Methylation (mesh), Humans (mesh), Epigenesis, Genetic (mesh), CpG Islands (mesh), Phenotype (mesh), Computational Biology (mesh), Adult (mesh), Epigenomics (mesh), Child (mesh), Machine Learning (mesh), Principal Component Analysis (mesh), Aging (mesh), Male (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix)
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Zdroj: Nature Communications. 16(1)
Témata: 3401 Analytical Chemistry (for-2020), 34 Chemical Sciences (for-2020), Lung (rcdc), Machine Learning and Artificial Intelligence (rcdc), Asthma (rcdc), Climate-Related Exposures and Conditions (rcdc), 2.1 Biological and endogenous factors (hrcs-rac), Respiratory (hrcs-hc), Machine Learning (mesh), Animals (mesh), Lipidomics (mesh), Female (mesh), Lung (mesh), Mice (mesh), Male (mesh), Ozone (mesh), Asthma (mesh), Lipids (mesh), Allergens (mesh), Humans (mesh), Mass Spectrometry (mesh), Mice, Inbred C57BL (mesh), Lung (mesh), Animals (mesh), Mice, Inbred C57BL (mesh), Humans (mesh), Mice (mesh), Asthma (mesh), Ozone (mesh), Lipids (mesh), Allergens (mesh), Female (mesh), Male (mesh), Mass Spectrometry (mesh), Machine Learning (mesh), Lipidomics (mesh), Machine Learning (mesh), Animals (mesh), Lipidomics (mesh), Female (mesh), Lung (mesh), Mice (mesh), Male (mesh), Ozone (mesh), Asthma (mesh), Lipids (mesh), Allergens (mesh), Humans (mesh), Mass Spectrometry (mesh), Mice, Inbred C57BL (mesh)
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