AIMC Topic: Denmark

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Mandatory surveillance of bacteremia conducted by automated monitoring.

Frontiers in public health Dec 16, 2024
Except for a few countries, comprehensive all-cause surveillance for bacteremia is not part of mandatory routine public health surveillance. We argue that time has come to include automated surveillance for bacteremia in the national surveillance sys...
Humans Population Surveillance Bacteremia Denmark Public Health Surveillance
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Individual risk assessment for rupture of abdominal aortic aneurysm using artificial intelligence.

Journal of vascular surgery Dec 13, 2024
OBJECTIVE: This study aimed to develop a prediction tool to identify abdominal aortic aneurysms (AAAs) at increased risk of rupture incorporating demographic, clinical, imaging, and medication data using artificial intelligence (AI).
Aged, 80 and over Male Middle Aged Risk Assessment Female Reproducibility of Results Risk Factors Aged Aortic Aneurysm, Abdominal Artificial Intelligence Case-Control Studies Humans Computed Tomography Angiography Decision Trees Decision Support Techniques Aortography Denmark Prognosis Aortic Rupture Predictive Value of Tests Retrospective Studies
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Validation of anorexia nervosa and Bulimia nervosa diagnosis coding in Danish hospitals assisted by a natural language processing model.

Journal of psychiatric research Sep 14, 2024
INTRODUCTION: The Danish Health Care Registers rely on the International Statistical Classification of Diseases and Related Health Problems (ICD)-classification and stand as a widely utilized resource for health epidemiological research. Eating disor...
Young Adult Adult Male Adolescent Humans Electronic Health Records Female Clinical Coding Anorexia Nervosa Bulimia Nervosa Denmark Natural Language Processing Registries International Classification of Diseases
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A deep learning approach to prediction of blood group antigens from genomic data.

Transfusion Sep 13, 2024
BACKGROUND: Deep learning methods are revolutionizing natural science. In this study, we aim to apply such techniques to develop blood type prediction models based on cheap to analyze and easily scalable screening array genotyping platforms.
Humans Blood Donors Finland Blood Group Antigens Deep Learning Genomics Genotype Denmark Neural Networks, Computer Female Male
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Using machine learning to unveil relevant predictors of adherence to recommended health-protective behaviors during the COVID-19 pandemic in Denmark.

Applied psychology. Health and well-being Jun 8, 2024
What were relevant predictors of individuals' proclivity to adhere to recommended health-protective behaviors during the COVID-19 pandemic in Denmark? Applying machine learning (namely, lasso regression) to a repeated cross-sectional survey spanning ...
Cross-Sectional Studies Male Middle Aged Health Knowledge, Attitudes, Practice Denmark Patient Compliance Health Behavior Female Humans Aged Machine Learning Young Adult COVID-19 Adult
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Role of artificial-intelligence-assisted automated cardiac biometrics in prenatal screening for coarctation of aorta.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Jun 3, 2024
OBJECTIVE: Although remarkable strides have been made in fetal medicine and the prenatal diagnosis of congenital heart disease, around 60% of newborns with isolated coarctation of the aorta (CoA) are not identified prior to birth. The prenatal detect...
Case-Control Studies ROC Curve Denmark Infant, Newborn Predictive Value of Tests Adult Humans Sensitivity and Specificity Artificial Intelligence Ultrasonography, Prenatal Gestational Age Pregnancy Biometry Female Fetal Heart Aortic Coarctation
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Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study.

BMC medical research methodology May 17, 2024
BACKGROUND: Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk ind...
Neural Networks, Computer Machine Learning Electronic Health Records Female Male Middle Aged Denmark Natural Language Processing Humans Smoking
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Development and Internal Validation of a Multivariable Prediction Model for Mortality After Hip Fracture with Machine Learning Techniques.

Calcified tissue international Apr 16, 2024
In order to estimate the likelihood of 1, 3, 6 and 12 month mortality in patients with hip fractures, we applied a variety of machine learning methods using readily available, preoperative data. We used prospectively collected data from a single univ...
ROC Curve Prospective Studies Denmark Prognosis Aged, 80 and over Hip Fractures Female Humans Male Aged Machine Learning Middle Aged
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Epidemiological description and trajectories of patients with prostate cancer in Denmark: an observational study of 7448 patients.

BMC research notes Nov 16, 2023
OBJECTIVE: Identification of patients at high risk of aggressive prostate cancer is a major clinical challenge. With the view of developing artificial intelligence-based methods for identification of these patients, we are constructing a comprehensiv...
Retrospective Studies Male Early Detection of Cancer Denmark Prostatic Neoplasms Humans Artificial Intelligence
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Population-wide evaluation of artificial intelligence and radiologist assessment of screening mammograms.

European radiology Nov 8, 2023
OBJECTIVES: To validate an AI system for standalone breast cancer detection on an entire screening population in comparison to first-reading breast radiologists.
Middle Aged Mass Screening Early Detection of Cancer Denmark Mammography Humans Aged Radiologists Sensitivity and Specificity Artificial Intelligence Breast Neoplasms Female
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