AIMC Journal:
Studies in health technology and informatics

Showing 771 to 780 of 1278 articles

Use of Natural Language Processing for Precise Retrieval of Key Elements of Health IT Evaluation Studies.

Studies in health technology and informatics Jun 26, 2020
Having precise information about health IT evaluation studies is important for evidence-based decisions in medical informatics. In a former feasibility study, we used a faceted search based on ontological modeling of key elements of studies to retrie...
Information Storage and Retrieval Natural Language Processing
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Using Machine Learning Algorithms to Predict Antimicrobial Resistance and Assist Empirical Treatment.

Studies in health technology and informatics Jun 26, 2020
Multi-drug-resistant (MDR) infections and their devastating consequences constitute a global problem and a constant threat to public health with immense costs for their treatment. Early identification of the pathogen and its antibiotic resistance pro...
Microbial Sensitivity Tests Machine Learning Drug Resistance, Bacterial Anti-Bacterial Agents Humans
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Semiautomated Approach for Muscle Weakness Detection in Clinical Texts.

Studies in health technology and informatics Jun 26, 2020
The automated detection of adverse events in medical records might be a cost-effective solution for patient safety management or pharmacovigilance. Our group proposed an information extraction algorithm (IEA) for detecting adverse events in neurosurg...
Humans Electronic Health Records Information Storage and Retrieval Pharmacovigilance Muscle Weakness Natural Language Processing
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Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in health technology and informatics Jun 26, 2020
Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to the healthcare system. However, real-time models specifically identifying readmissions related to hos...
Hospitals Patient Readmission Machine Learning Patient Safety Humans
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Unsupervised Machine Learning for the Discovery of Latent Clusters in COVID-19 Patients Using Electronic Health Records.

Studies in health technology and informatics Jun 26, 2020
The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent clusters in COVID-19 patients. Over 6,000 adult patients tested positive for the SARS-CoV-2 infection at the Mount Sinai Health System in New...
Humans Pneumonia, Viral Unsupervised Machine Learning Betacoronavirus SARS-CoV-2 COVID-19 Electronic Health Records Pandemics New York Coronavirus Infections
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Evaluation of Different Learning Algorithms of Neural Networks for Drug Dosing Recommendations in Pediatrics.

Studies in health technology and informatics Jun 23, 2020
Publicly accessible databases with evidence-based information on drug dosages for children and adolescents are not available in Germany. In previous work a prototypical web-based online platform for pediatric dosing recommendation has been developed....
Child Germany Adolescent Neural Networks, Computer Algorithms Machine Learning Humans
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Mobile Robotic Telepresence Between Hospital and School: Lessons Learned.

Studies in health technology and informatics Jun 23, 2020
If a pupil falls seriously ill, it is not only a shock for the pupil himself or herself, but also for his or her family and classmates. The project "Virtual Classroom" of the Heilbronn University in cooperation with the foundation "Big Help for Littl...
User-Computer Interface Robotics Hospitals Humans Schools
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Experimenting with Generative Adversarial Networks to Expand Sparse Physiological Time-Series Data.

Studies in health technology and informatics Jun 23, 2020
Machine Learning research and its application have gained enormous relevance in recent years. Their usage in medical settings could support patients, increase patient safety and assist health professionals in various tasks. However, medical data is o...
Machine Learning Data Science
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Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients.

Studies in health technology and informatics Jun 23, 2020
Delirium is an acute mental disturbance that particularly occurs during hospital stay. Current clinical assessment instruments include the Delirium Observation Screening Scale (DOSS) or the Confusion Assessment Method (CAM). The aim of this work is t...
International Classification of Diseases Humans Delirium Machine Learning
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Neural Networks for Cause of Hospitalization and Final Cause of Death Extraction from Discharge Summaries.

Studies in health technology and informatics Jun 16, 2020
Determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost importance. This is usually recorded in free text form. In this study we aimed to develop a series of supervised natural language processing algorith...
Humans Neural Networks, Computer Cause of Death Patient Discharge Natural Language Processing Hospitalization
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