Suchergebnisse - "Bayes Theorem [MeSH]"
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1
Autoren: Wali, Behram
Quelle: Health & Place. 95
Schlagwörter: 4406 Human Geography (for-2020), 4206 Public Health (for-2020), 42 Health Sciences (for-2020), 44 Human Society (for-2020), Cardiovascular (rcdc), Behavioral and Social Science (rcdc), Heart Disease (rcdc), Clinical Research (rcdc), Cardiovascular (hrcs-hc), 15 Life on Land (sdg), 3 Good Health and Well Being (sdg), Cardiovascular disease, Hypertension, Built environment, Full Bayes estimation, Markov chain Monte Carlo, Random parameters, Humans (mesh), Cardiovascular Diseases (mesh), Walking (mesh), Prevalence (mesh), Bayes Theorem (mesh), Longitudinal Studies (mesh), Cities (mesh), Environment Design (mesh), Residence Characteristics (mesh), Social Environment (mesh), Transportation (mesh), Middle Aged (mesh), United States (mesh), Female (mesh), Male (mesh), Built Environment (mesh), Neighborhood Characteristics (mesh), Built environment, Cardiovascular disease, Full Bayes estimation, Hypertension, Markov chain Monte Carlo, Random parameters, Humans (mesh), Built Environment (mesh), Cardiovascular Diseases (mesh), Longitudinal Studies (mesh), Neighborhood Characteristics (mesh), Residence Characteristics (mesh), Walking (mesh), Prevalence (mesh), Bayes Theorem (mesh), Male (mesh), Transportation (mesh), Female (mesh), Cities (mesh), United States (mesh), Social Environment (mesh), Environment Design (mesh), Middle Aged (mesh), 1117 Public Health and Health Services (for), 1604 Human Geography (for), Public Health (science-metrix), 42 Health sciences (for-2020), 44 Human society (for-2020)
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2
Autoren: et al.
Quelle: Journal of the Association of Nurses in AIDS Care. 36(3)
Schlagwörter: 4203 Health Services and Systems (for-2020), 42 Health Sciences (for-2020), Infectious Diseases (rcdc), Behavioral and Social Science (rcdc), Mental Health (rcdc), Clinical Research (rcdc), HIV/AIDS (rcdc), Prevention (rcdc), Health Services (rcdc), Social Determinants of Health (rcdc), Sexually Transmitted Infections (rcdc), Mental health (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), HIV Infections (mesh), Male (mesh), Female (mesh), Adult (mesh), Ill-Housed Persons (mesh), Middle Aged (mesh), Patient Preference (mesh), Mobile Health Units (mesh), Surveys and Questionnaires (mesh), Health Services Accessibility (mesh), Patient Satisfaction (mesh), Bayes Theorem (mesh), care engagement, health services preferences, maximum difference, mobile health clinic, preference methods, vulnerable populations, Humans (mesh), HIV Infections (mesh), Bayes Theorem (mesh), Adult (mesh), Middle Aged (mesh), Mobile Health Units (mesh), Patient Satisfaction (mesh), Health Services Accessibility (mesh), Female (mesh), Male (mesh), Patient Preference (mesh), Surveys and Questionnaires (mesh), Ill-Housed Persons (mesh), care engagement, health services preferences, maximum difference, mobile health clinic, preference methods, vulnerable populations, Humans (mesh), HIV Infections (mesh), Male (mesh), Female (mesh), Adult (mesh), Ill-Housed Persons (mesh), Middle Aged (mesh), Patient Preference (mesh), Mobile Health Units (mesh), Surveys and Questionnaires (mesh), Health Services Accessibility (mesh), Patient Satisfaction (mesh), Bayes Theorem (mesh), 1110 Nursing (for), Public Health (science-metrix), 4205 Nursing (for-2020)
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3
Autoren: et al.
Quelle: British Journal of Ophthalmology. 109(3)
Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3212 Ophthalmology and Optometry (for-2020), Eye Disease and Disorders of Vision (rcdc), Neurosciences (rcdc), Pediatric (rcdc), Humans (mesh), Tomography, Optical Coherence (mesh), Male (mesh), Female (mesh), Retrospective Studies (mesh), Adult (mesh), Usher Syndromes (mesh), Middle Aged (mesh), Extracellular Matrix Proteins (mesh), Visual Acuity (mesh), Follow-Up Studies (mesh), Young Adult (mesh), Disease Progression (mesh), Adolescent (mesh), Retinal Diseases (mesh), Retina (mesh), Bayes Theorem (mesh), Aged (mesh), Imaging, Retina, Degeneration, Epidemiology, Retina (mesh), Humans (mesh), Retinal Diseases (mesh), Disease Progression (mesh), Extracellular Matrix Proteins (mesh), Tomography, Optical Coherence (mesh), Bayes Theorem (mesh), Retrospective Studies (mesh), Follow-Up Studies (mesh), Visual Acuity (mesh), Adolescent (mesh), Adult (mesh), Aged (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Usher Syndromes (mesh), Young Adult (mesh), Degeneration, Epidemiology, Imaging, Retina, Humans (mesh), Tomography, Optical Coherence (mesh), Male (mesh), Female (mesh), Retrospective Studies (mesh), Adult (mesh), Usher Syndromes (mesh), Middle Aged (mesh), Extracellular Matrix Proteins (mesh), Visual Acuity (mesh), Follow-Up Studies (mesh), Young Adult (mesh), Disease Progression (mesh), Adolescent (mesh), Retinal Diseases (mesh), Retina (mesh), Bayes Theorem (mesh), Aged (mesh), 1103 Clinical Sciences (for), 1113 Opthalmology and Optometry (for), 1117 Public Health and Health Services (for), Ophthalmology & Optometry (science-metrix), 3202 Clinical sciences (for-2020), 3212 Ophthalmology and optometry (for-2020)
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4
Autoren: et al.
Quelle: Epidemiology. 36(2)
Schlagwörter: 4206 Public Health (for-2020), 42 Health Sciences (for-2020), Women's Health (rcdc), Mental Illness (rcdc), Serious Mental Illness (rcdc), Alcoholism, Alcohol Use and Health (rcdc), Cannabinoid Research (rcdc), Behavioral and Social Science (rcdc), Substance Misuse (rcdc), Brain Disorders (rcdc), Physical Injury - Accidents and Adverse Effects (rcdc), Mental Health (rcdc), 3 Good Health and Well Being (sdg), Humans (mesh), California (mesh), Self-Injurious Behavior (mesh), Adult (mesh), Female (mesh), Male (mesh), Spatio-Temporal Analysis (mesh), Adolescent (mesh), Young Adult (mesh), Middle Aged (mesh), Commerce (mesh), Alcoholic Beverages (mesh), Cannabis (mesh), Alcohol Drinking (mesh), Bayes Theorem (mesh), Child (mesh), Alcohol, California, Cannabis, Marijuana, Outlet density, Policy, Self-harm, Suicide, Humans (mesh), Cannabis (mesh), Bayes Theorem (mesh), Self-Injurious Behavior (mesh), Alcohol Drinking (mesh), Commerce (mesh), Alcoholic Beverages (mesh), Adolescent (mesh), Adult (mesh), Middle Aged (mesh), Child (mesh), California (mesh), Female (mesh), Male (mesh), Young Adult (mesh), Spatio-Temporal Analysis (mesh), Humans (mesh), California (mesh), Self-Injurious Behavior (mesh), Adult (mesh), Female (mesh), Male (mesh), Spatio-Temporal Analysis (mesh), Adolescent (mesh), Young Adult (mesh), Middle Aged (mesh), Commerce (mesh), Alcoholic Beverages (mesh), Cannabis (mesh), Alcohol Drinking (mesh), Bayes Theorem (mesh), Child (mesh), 0104 Statistics (for), 1117 Public Health and Health Services (for), Epidemiology (science-metrix), 4202 Epidemiology (for-2020), 4206 Public health (for-2020), 4905 Statistics (for-2020)
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5
Autoren: et al.
Quelle: Journal of the International AIDS Society. 27(12)
Schlagwörter: 3207 Medical Microbiology (for-2020), 32 Biomedical and Clinical Sciences (for-2020), HIV/AIDS (rcdc), Rare Diseases (rcdc), Infectious Diseases (rcdc), Clinical Research (rcdc), Prevention (rcdc), Emerging Infectious Diseases (rcdc), Sexually Transmitted Infections (rcdc), Tuberculosis (rcdc), 6.1 Pharmaceuticals (hrcs-rac), Infection (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), Female (mesh), Uganda (mesh), Male (mesh), Adult (mesh), HIV Infections (mesh), Tuberculosis (mesh), Middle Aged (mesh), Antitubercular Agents (mesh), Patient Preference (mesh), Isoniazid (mesh), Bayes Theorem (mesh), Choice Behavior (mesh), Young Adult (mesh), TB, Uganda, values and preferences, latent tuberculosis infection, tuberculosis preventive treatment, person-centred care, Humans (mesh), Tuberculosis (mesh), HIV Infections (mesh), Isoniazid (mesh), Antitubercular Agents (mesh), Bayes Theorem (mesh), Choice Behavior (mesh), Adult (mesh), Middle Aged (mesh), Uganda (mesh), Female (mesh), Male (mesh), Young Adult (mesh), Patient Preference (mesh), TB, Uganda, latent tuberculosis infection, person‐centred care, tuberculosis preventive treatment, values and preferences, Humans (mesh), Female (mesh), Uganda (mesh), Male (mesh), Adult (mesh), HIV Infections (mesh), Tuberculosis (mesh), Middle Aged (mesh), Antitubercular Agents (mesh), Patient Preference (mesh), Isoniazid (mesh), Bayes Theorem (mesh), Choice Behavior (mesh), Young Adult (mesh), 1103 Clinical Sciences (for), 1117 Public Health and Health Services (for), 1199 Other Medical and Health Sciences (for), 3202 Clinical sciences (for-2020), 4202 Epidemiology (for-2020), 4206 Public health (for-2020)
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6
Autoren: et al.
Quelle: AIDS and Behavior. 28(12)
Schlagwörter: 4206 Public Health (for-2020), 42 Health Sciences (for-2020), Social Determinants of Health (rcdc), Health Services (rcdc), Substance Misuse (rcdc), Clinical Research (rcdc), Sexually Transmitted Infections (rcdc), Infectious Diseases (rcdc), Mental Health (rcdc), Clinical Trials and Supportive Activities (rcdc), Prevention (rcdc), Behavioral and Social Science (rcdc), Drug Abuse (NIDA only) (rcdc), HIV/AIDS (rcdc), 3 Good Health and Well Being (sdg), Adolescent (mesh), Adult (mesh), Humans (mesh), Male (mesh), Young Adult (mesh), Bayes Theorem (mesh), Cluster Analysis (mesh), HIV Infections (mesh), Risk Reduction Behavior (mesh), Risk-Taking (mesh), Sexual Behavior (mesh), Soccer (mesh), South Africa (mesh), Substance-Related Disorders (mesh), Vocational Education (mesh), Prevention, Soccer, Vocational training, HIV, Substance abuse, Cluster randomized controlled trial, Young men, South Africa, Humans (mesh), HIV Infections (mesh), Substance-Related Disorders (mesh), Cluster Analysis (mesh), Bayes Theorem (mesh), Risk Reduction Behavior (mesh), Risk-Taking (mesh), Sexual Behavior (mesh), Vocational Education (mesh), Soccer (mesh), Adolescent (mesh), Adult (mesh), South Africa (mesh), Male (mesh), Young Adult (mesh), Cluster randomized controlled trial, HIV, Prevention, Soccer, South Africa, Substance abuse, Vocational training, Young men, Adolescent (mesh), Adult (mesh), Humans (mesh), Male (mesh), Young Adult (mesh), Bayes Theorem (mesh), Cluster Analysis (mesh), HIV Infections (mesh), Risk Reduction Behavior (mesh), Risk-Taking (mesh), Sexual Behavior (mesh), Soccer (mesh), South Africa (mesh), Substance-Related Disorders (mesh), Vocational Education (mesh), 1117 Public Health and Health Services (for), 1607 Social Work (for), Public Health (science-metrix), 4206 Public health (for-2020)
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7
Autoren: et al.
Quelle: Nature, vol 645, iss 8079
Schlagwörter: Inbred C57BL (mesh), General Science & Technology (science-metrix), Bayes Theorem (mesh), Decision Making (mesh), Mice (mesh), Probability (mesh), Photic Stimulation (mesh), Brain (mesh), Mice, Calcium (mesh), Models, Female (mesh), Animals (mesh), Neurological (mesh), Male (mesh), International Brain Laboratory
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8
Autoren: et al.
Quelle: Clinical and Translational Medicine. 14(3)
Schlagwörter: 4205 Nursing (for-2020), 42 Health Sciences (for-2020), Urologic Diseases (rcdc), Aging (rcdc), Cancer (rcdc), Prostate Cancer (rcdc), Clinical Research (rcdc), Clinical Trials and Supportive Activities (rcdc), 6.1 Pharmaceuticals (hrcs-rac), Cancer (hrcs-hc), Male (mesh), Humans (mesh), Docetaxel (mesh), Prostatic Neoplasms (mesh), Lycopene (mesh), Vascular Endothelial Growth Factor A (mesh), Androgen Antagonists (mesh), Androgens (mesh), Bayes Theorem (mesh), Endothelial Cells (mesh), docetaxel, lycopene, phase I trial, prostate cancer, docetaxel, lycopene, phase I trial, prostate cancer, Endothelial Cells (mesh), Humans (mesh), Prostatic Neoplasms (mesh), Androgen Antagonists (mesh), Vascular Endothelial Growth Factor A (mesh), Androgens (mesh), Bayes Theorem (mesh), Male (mesh), Docetaxel (mesh), Lycopene (mesh), docetaxel, lycopene, phase I trial, prostate cancer, Male (mesh), Humans (mesh), Docetaxel (mesh), Prostatic Neoplasms (mesh), Lycopene (mesh), Vascular Endothelial Growth Factor A (mesh), Androgen Antagonists (mesh), Androgens (mesh), Bayes Theorem (mesh), Endothelial Cells (mesh), 1110 Nursing (for), 4205 Nursing (for-2020)
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9
Autoren: et al.
Quelle: The Lancet Digital Health. 6(3)
Schlagwörter: 4206 Public Health (for-2020), 42 Health Sciences (for-2020), HIV/AIDS (rcdc), Infectious Diseases (rcdc), Pediatric AIDS (rcdc), Sexual and Gender Minorities (SGM/LGBT*) (rcdc), Women's Health (rcdc), Behavioral and Social Science (rcdc), Sexually Transmitted Infections (rcdc), Pediatric (rcdc), Health Disparities (rcdc), Clinical Trials and Supportive Activities (rcdc), Prevention (rcdc), Clinical Research (rcdc), Social Determinants of Health (rcdc), Minority Health (rcdc), Adolescent Sexual Activity (rcdc), 3.1 Primary prevention interventions to modify behaviours or promote wellbeing (hrcs-rac), 7.1 Individual care needs (hrcs-rac), Infection (hrcs-hc), 3 Good Health and Well Being (sdg), Adolescent (mesh), Humans (mesh), Male (mesh), Female (mesh), United States (mesh), Homosexuality, Male (mesh), HIV Infections (mesh), Acquired Immunodeficiency Syndrome (mesh), Bayes Theorem (mesh), Sexual and Gender Minorities (mesh), Adolescent HIV Medicine Trials Network (ATN) CARES Study Team, Humans (mesh), HIV Infections (mesh), Acquired Immunodeficiency Syndrome (mesh), Bayes Theorem (mesh), Homosexuality, Male (mesh), Adolescent (mesh), United States (mesh), Female (mesh), Male (mesh), Sexual and Gender Minorities (mesh), Adolescent (mesh), Humans (mesh), Male (mesh), Female (mesh), United States (mesh), Homosexuality, Male (mesh), HIV Infections (mesh), Acquired Immunodeficiency Syndrome (mesh), Bayes Theorem (mesh), Sexual and Gender Minorities (mesh), 4203 Health services and systems (for-2020)
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10
Autoren: et al.
Quelle: Clinical Lung Cancer. 25(2)
Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), 3211 Oncology and Carcinogenesis (for-2020), Cancer (rcdc), Clinical Trials and Supportive Activities (rcdc), Lung (rcdc), Clinical Research (rcdc), Patient Safety (rcdc), Heart Disease (rcdc), Rare Diseases (rcdc), Cardiovascular (rcdc), Lung Cancer (rcdc), Orphan Drug (rcdc), Women's Health (rcdc), Radiation Oncology (rcdc), 6.5 Radiotherapy and other non-invasive therapies (hrcs-rac), 6.1 Pharmaceuticals (hrcs-rac), Cardiovascular (hrcs-hc), Cancer (hrcs-hc), 3 Good Health and Well Being (sdg), Humans (mesh), Adolescent (mesh), Lung Neoplasms (mesh), Carcinoma, Non-Small-Cell Lung (mesh), Bayes Theorem (mesh), Chemoradiotherapy (mesh), Lung (mesh), Antineoplastic Combined Chemotherapy Protocols (mesh), Clinical Trials, Phase II as Topic (mesh), Clinical Trials, Phase I as Topic (mesh), Clinical trial, Isotoxic radiation, Dose escalation, Personalized medicine, Personalized radiation, Lung (mesh), Humans (mesh), Carcinoma, Non-Small-Cell Lung (mesh), Lung Neoplasms (mesh), Antineoplastic Combined Chemotherapy Protocols (mesh), Bayes Theorem (mesh), Adolescent (mesh), Clinical Trials, Phase I as Topic (mesh), Clinical Trials, Phase II as Topic (mesh), Chemoradiotherapy (mesh), Clinical trial, Dose escalation, Isotoxic radiation, Personalized medicine, Personalized radiation, Humans (mesh), Adolescent (mesh), Lung Neoplasms (mesh), Carcinoma, Non-Small-Cell Lung (mesh), Bayes Theorem (mesh), Chemoradiotherapy (mesh), Lung (mesh), Antineoplastic Combined Chemotherapy Protocols (mesh), Clinical Trials, Phase II as Topic (mesh), Clinical Trials, Phase I as Topic (mesh), 1103 Clinical Sciences (for), 1112 Oncology and Carcinogenesis (for), Oncology & Carcinogenesis (science-metrix), 3202 Clinical sciences (for-2020), 3211 Oncology and carcinogenesis (for-2020)
Dateibeschreibung: application/pdf
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11
Autoren: et al.
Quelle: Communications Biology. 7(1)
Schlagwörter: 31 Biological Sciences (for-2020), 32 Biomedical and Clinical Sciences (for-2020), Basic Behavioral and Social Science (rcdc), Behavioral and Social Science (rcdc), Mental Health (rcdc), Biomedical Imaging (rcdc), Neurosciences (rcdc), Humans (mesh), Brain (mesh), Neuroimaging (mesh), Adolescent (mesh), Algorithms (mesh), Bayes Theorem (mesh), Female (mesh), Male (mesh), Magnetic Resonance Imaging (mesh), Models, Statistical (mesh), Child (mesh), Brain (mesh), Humans (mesh), Magnetic Resonance Imaging (mesh), Models, Statistical (mesh), Bayes Theorem (mesh), Algorithms (mesh), Adolescent (mesh), Child (mesh), Female (mesh), Male (mesh), Neuroimaging (mesh), Humans (mesh), Brain (mesh), Neuroimaging (mesh), Adolescent (mesh), Algorithms (mesh), Bayes Theorem (mesh), Female (mesh), Male (mesh), Magnetic Resonance Imaging (mesh), Models, Statistical (mesh), Child (mesh), 31 Biological sciences (for-2020), 32 Biomedical and clinical sciences (for-2020)
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12
Autoren: et al.
Quelle: PLOS ONE. 19(3)
Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3203 Dentistry (for-2020), Prevention (rcdc), Infectious Diseases (rcdc), Pediatric (rcdc), Machine Learning and Artificial Intelligence (rcdc), Clinical Research (rcdc), Dental/Oral and Craniofacial Disease (rcdc), Bioengineering (rcdc), Health Disparities (rcdc), Oral and gastrointestinal (hrcs-hc), Humans (mesh), Dental Caries (mesh), Cross-Sectional Studies (mesh), Bayes Theorem (mesh), Surveys and Questionnaires (mesh), Machine Learning (mesh), Humans (mesh), Dental Caries (mesh), Bayes Theorem (mesh), Cross-Sectional Studies (mesh), Machine Learning (mesh), Surveys and Questionnaires (mesh), Humans (mesh), Dental Caries (mesh), Cross-Sectional Studies (mesh), Bayes Theorem (mesh), Surveys and Questionnaires (mesh), Machine Learning (mesh), General Science & Technology (science-metrix)
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13
Autoren: et al.
Quelle: Arch Toxicol
Schlagwörter: 0301 basic medicine, In Vitro Systems, 0303 health sciences, 03 medical and health sciences, Dose-Response Relationship, Drug [MeSH], Optimal design, Humans [MeSH], Concentration-response experiments, Valproic Acid/administration, Cell Survival/drug effects [MeSH], Bayesian optimal design, Valproic Acid/toxicity [MeSH], Bayes Theorem [MeSH], Research Design [MeSH], Toxicity Tests/methods [MeSH]
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14
Autoren: et al.
Quelle: Adv Ther
Schlagwörter: Biological Products, Network Meta-Analysis, Remission Induction, Adalimumab, Bayes Theorem, Severity of Illness Index, Treatment Outcome, Gastrointestinal Agents, Humans, Janus Kinase Inhibitors, Colitis, Ulcerative, Colitis, Ulcerative/diagnosis [MeSH], Biologics, IL-23 inhibitors, Humans [MeSH], Severity of Illness Index [MeSH], Treatment Outcome [MeSH], Adalimumab/adverse effects [MeSH], Janus Kinase Inhibitors/administration, Advanced therapies, Bayes Theorem [MeSH], Comparative efficacy, Gastrointestinal Agents/adverse effects [MeSH], Janus Kinase Inhibitors/adverse effects [MeSH], Randomized Controlled Trials as Topic [MeSH], Colitis, Ulcerative/drug therapy [MeSH], Small molecules, Adalimumab/administration, Biological Products/administration, Biological Products/adverse effects [MeSH], Remission Induction/methods [MeSH], Original Research, Ulcerative colitis, Gastrointestinal Agents/administration, Mirikizumab, Randomized Controlled Trials as Topic
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15
Autoren: et al.
Quelle: Cancer Chemother Pharmacol
Cancer Chemotherapy and Pharmacology, 94, 6, pp. 799-806Schlagwörter: Male, Adult, Lung Neoplasms, Nephrology - Radboud University Medical Center, Intensive Care - Radboud University Medical Center, Antineoplastic Agents, Bayes Theorem, Pemetrexed, Enkephalins, Middle Aged, Kidney Function Tests, Kidney, Models, Biological, Kidney/drug effects [MeSH], Antineoplastic Agents/adverse effects [MeSH], Aged [MeSH], Antineoplastic Agents/administration, Bayes Theorem [MeSH], Models, Biological [MeSH], Cystatin C/blood [MeSH], Renal function, Biomarker, Male [MeSH], Creatinine/blood [MeSH], Pemetrexed/pharmacokinetics [MeSH], Female [MeSH], Adult [MeSH], Biomarkers/blood [MeSH], GFR, Kidney/metabolism [MeSH], Humans [MeSH], Protein Precursors/blood [MeSH], Middle Aged [MeSH], Kidney Function Tests/methods [MeSH], Antineoplastic Agents/pharmacokinetics [MeSH], Enkephalins/blood [MeSH], Pharmacokinetics, Pemetrexed/administration, Lung cancer, Chemotherapy, Lung Neoplasms/drug therapy [MeSH], Original Article, Creatinine, Humans, Female, Cystatin C, Protein Precursors, Pulmonary Diseases - Radboud University Medical Center, Biomarkers, Pharmacy, Pharmacology and Toxicology - Radboud University Medical Center, Aged
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16
Autoren: et al.
Quelle: Nature Protocols. 18(12)
Schlagwörter: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Data Science (rcdc), Bioengineering (rcdc), Generic health relevance (hrcs-hc), Bayes Theorem (mesh), Algorithms (mesh), Programming Languages (mesh), Single-Cell Analysis (mesh), Bayes Theorem (mesh), Algorithms (mesh), Programming Languages (mesh), Single-Cell Analysis (mesh), Bayes Theorem (mesh), Algorithms (mesh), Programming Languages (mesh), Single-Cell Analysis (mesh), 03 Chemical Sciences (for), 06 Biological Sciences (for), 11 Medical and Health Sciences (for), Bioinformatics (science-metrix)
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17
Autoren: et al.
Quelle: AIDS. 37(9)
Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 4206 Public Health (for-2020), 42 Health Sciences (for-2020), Social Determinants of Health (rcdc), Women's Health (rcdc), Infectious Diseases (rcdc), Health Disparities (rcdc), Sexually Transmitted Infections (rcdc), Minority Health (rcdc), Behavioral and Social Science (rcdc), HIV/AIDS (rcdc), Clinical Research (rcdc), Infection (hrcs-hc), Humans (mesh), Female (mesh), HIV Infections (mesh), Los Angeles (mesh), Bayes Theorem (mesh), Ethnicity (mesh), Racial Groups (mesh), disparities, gender, HIV, psychosocial health, public health programs, race, viral suppression, Humans (mesh), HIV Infections (mesh), Bayes Theorem (mesh), Los Angeles (mesh), Female (mesh), Ethnicity (mesh), Racial Groups (mesh), Humans (mesh), Female (mesh), HIV Infections (mesh), Los Angeles (mesh), Bayes Theorem (mesh), Ethnicity (mesh), Racial Groups (mesh), 06 Biological Sciences (for), 11 Medical and Health Sciences (for), 17 Psychology and Cognitive Sciences (for), Virology (science-metrix), 32 Biomedical and clinical sciences (for-2020), 42 Health sciences (for-2020)
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18
Autoren: et al.
Quelle: Environmental Research. 229
Schlagwörter: 41 Environmental Sciences (for-2020), 4105 Pollution and Contamination (for-2020), Brain Disorders (rcdc), Endocrine Disruptors (rcdc), Mental Health (rcdc), Pediatric (rcdc), Behavioral and Social Science (rcdc), Autism (rcdc), Intellectual and Developmental Disabilities (IDD) (rcdc), Neurosciences (rcdc), Clinical Research (rcdc), Pregnancy (mesh), Child (mesh), Female (mesh), Humans (mesh), Child, Preschool (mesh), Persistent Organic Pollutants (mesh), Prenatal Exposure Delayed Effects (mesh), Dichlorodiphenyl Dichloroethylene (mesh), Autism Spectrum Disorder (mesh), Halogenated Diphenyl Ethers (mesh), Bayes Theorem (mesh), Polychlorinated Biphenyls (mesh), Environmental Pollutants (mesh), Sociological Factors (mesh), Cognition (mesh), Persistent organic pollutants, Autism-related traits, Environmental mixture, Bayesian kernel machine regression, Quantile g-computation, Humans (mesh), Prenatal Exposure Delayed Effects (mesh), Polychlorinated Biphenyls (mesh), Dichlorodiphenyl Dichloroethylene (mesh), Environmental Pollutants (mesh), Bayes Theorem (mesh), Cognition (mesh), Pregnancy (mesh), Child (mesh), Child, Preschool (mesh), Female (mesh), Halogenated Diphenyl Ethers (mesh), Sociological Factors (mesh), Autism Spectrum Disorder (mesh), Persistent Organic Pollutants (mesh), Autism-related traits, Bayesian kernel machine regression, Environmental mixture, Persistent organic pollutants, Quantile g-computation, Pregnancy (mesh), Child (mesh), Female (mesh), Humans (mesh), Child, Preschool (mesh), Persistent Organic Pollutants (mesh), Prenatal Exposure Delayed Effects (mesh), Dichlorodiphenyl Dichloroethylene (mesh), Autism Spectrum Disorder (mesh), Halogenated Diphenyl Ethers (mesh), Bayes Theorem (mesh), Polychlorinated Biphenyls (mesh), Environmental Pollutants (mesh), Sociological Factors (mesh), Cognition (mesh), 03 Chemical Sciences (for), 05 Environmental Sciences (for), 06 Biological Sciences (for), Toxicology (science-metrix), 31 Biological sciences (for-2020), 34 Chemical sciences (for-2020), 41 Environmental sciences (for-2020)
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19
Autoren: et al.
Quelle: Int J Legal Med
Schlagwörter: Adolescent [MeSH], Bayesian theorem, Female [MeSH], Biological variation, Forensic anthropology, Humans [MeSH], Molar, Third/diagnostic imaging [MeSH], Bayes Theorem [MeSH], Molar, Third/growth, Original Article, Male [MeSH], Clavicle/diagnostic imaging [MeSH], Validation study, Models, Statistical [MeSH], Young Adult [MeSH], Age Determination by Skeleton/methods [MeSH], Population, Age Determination by Teeth/methods [MeSH], Age distribution
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20
Autoren: et al.
Quelle: Environmental Health Perspectives. 131(6)
Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 4202 Epidemiology (for-2020), 4206 Public Health (for-2020), 42 Health Sciences (for-2020), 3210 Nutrition and Dietetics (for-2020), Endocrine Disruptors (rcdc), Prevention (rcdc), Pediatric (rcdc), Clinical Research (rcdc), Childhood Obesity (rcdc), Obesity (rcdc), Nutrition (rcdc), Women's Health (rcdc), 2.1 Biological and endogenous factors (hrcs-rac), Oral and gastrointestinal (hrcs-hc), Cardiovascular (hrcs-hc), Metabolic and endocrine (hrcs-hc), Cancer (hrcs-hc), Male (mesh), Pregnancy (mesh), Female (mesh), Adolescent (mesh), Humans (mesh), Child, Preschool (mesh), Child (mesh), Body Mass Index (mesh), Overweight (mesh), Prospective Studies (mesh), Bayes Theorem (mesh), Obesity (mesh), Fluorocarbons (mesh), Environmental Pollutants (mesh), Alkanesulfonic Acids (mesh), the program collaborators for Environmental influences on Child Health Outcomes, Humans (mesh), Obesity (mesh), Alkanesulfonic Acids (mesh), Fluorocarbons (mesh), Environmental Pollutants (mesh), Body Mass Index (mesh), Bayes Theorem (mesh), Prospective Studies (mesh), Pregnancy (mesh), Adolescent (mesh), Child (mesh), Child, Preschool (mesh), Female (mesh), Male (mesh), Overweight (mesh), Male (mesh), Pregnancy (mesh), Female (mesh), Adolescent (mesh), Humans (mesh), Child, Preschool (mesh), Child (mesh), Body Mass Index (mesh), Overweight (mesh), Prospective Studies (mesh), Bayes Theorem (mesh), Obesity (mesh), Fluorocarbons (mesh), Environmental Pollutants (mesh), Alkanesulfonic Acids (mesh), 05 Environmental Sciences (for), 11 Medical and Health Sciences (for), Toxicology (science-metrix), 32 Biomedical and clinical sciences (for-2020), 41 Environmental sciences (for-2020), 42 Health sciences (for-2020)
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