AIMC Topic: Machine Learning

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Predicting outcomes in central venous catheter salvage in pediatric central line-associated bloodstream infection.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: Central line-associated bloodstream infections (CLABSIs) are a common, costly, and hazardous healthcare-associated infection in children. In children in whom continued access is critical, salvage of infected central venous catheters (CVCs)...
Cross Infection Recurrence ROC Curve Treatment Outcome Area Under Curve Central Venous Catheters Adolescent Child, Preschool Female Child Male Humans Infant Machine Learning Sepsis Anti-Infective Agents Prognosis
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Recommendations for the safe, effective use of adaptive CDS in the US healthcare system: an AMIA position paper.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
The development and implementation of clinical decision support (CDS) that trains itself and adapts its algorithms based on new data-here referred to as Adaptive CDS-present unique challenges and considerations. Although Adaptive CDS represents an ex...
Humans Artificial Intelligence Machine Learning Algorithms Delivery of Health Care Decision Support Systems, Clinical United States Health Policy Medical Informatics Organizational Policy Societies, Medical
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Application of Bayesian networks to generate synthetic health data.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: This study seeks to develop a fully automated method of generating synthetic data from a real dataset that could be employed by medical organizations to distribute health data to researchers, reducing the need for access to real data. We h...
Datasets as Topic Neural Networks, Computer Disclosure Machine Learning Data Management Bayes Theorem Confidentiality Data Anonymization Information Dissemination Humans
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A comparison of general and disease-specific machine learning models for the prediction of unplanned hospital readmissions.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
Unplanned hospital readmissions are a burden to patients and increase healthcare costs. A wide variety of machine learning (ML) models have been suggested to predict unplanned hospital readmissions. These ML models were often specifically trained on ...
Humans Patient Readmission Datasets as Topic Neoplasms Cohort Studies Treatment Outcome Models, Statistical Chronic Disease Area Under Curve Tertiary Care Centers Lung Diseases Female Machine Learning Hospitalization Prognosis Male Electronic Health Records Cardiovascular Diseases
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On collaborative reinforcement learning to optimize the redistribution of critical medical supplies throughout the COVID-19 pandemic.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: This work investigates how reinforcement learning and deep learning models can facilitate the near-optimal redistribution of medical equipment in order to bolster public health responses to future crises similar to the COVID-19 pandemic.
COVID-19 Algorithms Deep Learning Equipment and Supplies Machine Learning Pandemics Resource Allocation Public Health Administration
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A Machine Learning Algorithm to Identify Patients with Tibial Shaft Fractures at Risk for Infection After Operative Treatment.

The Journal of bone and joint surgery. American volume Mar 17, 2021
BACKGROUND: Risk stratification of individual patients who are prone to infection would allow surgeons to monitor high-risk patients more closely and intervene early when needed. This could reduce infection-related consequences such as increased heal...
Tibia Tibial Fractures Prosthesis-Related Infections Middle Aged Risk Assessment Adolescent Anti-Bacterial Agents Female Risk Factors Aged Aged, 80 and over Young Adult Adult Male Humans Machine Learning Algorithms
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Synthetic heparan sulfate standards and machine learning facilitate the development of solid-state nanopore analysis.

Proceedings of the National Academy of Sciences of the United States of America Mar 16, 2021
The application of solid-state (SS) nanopore devices to single-molecule nucleic acid sequencing has been challenging. Thus, the early successes in applying SS nanopore devices to the more difficult class of biopolymer, glycosaminoglycans (GAGs), have...
Carbohydrate Sequence Machine Learning Disaccharides Heparitin Sulfate Glycomics Monosaccharides Nanopores
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Predicting Discharge Disposition Following Meningioma Resection Using a Multi-Institutional Natural Language Processing Model.

Neurosurgery Mar 15, 2021
BACKGROUND: Machine learning (ML)-based predictive models are increasingly common in neurosurgery, but typically require large databases of discrete variables for training. Natural language processing (NLP) can extract meaningful data from unstructur...
Humans Machine Learning Natural Language Processing Algorithms Retrospective Studies Databases, Factual Patient Discharge Female Meningioma Male Aged Meningeal Neoplasms Adult Middle Aged Predictive Value of Tests
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Machine Learning Prediction of SARS-CoV-2 Polymerase Chain Reaction Results with Routine Blood Tests.

Laboratory medicine Mar 15, 2021
OBJECTIVE: The diagnosis of COVID-19 is based on the detection of SARS-CoV-2 in respiratory secretions, blood, or stool. Currently, reverse transcription polymerase chain reaction (RT-PCR) is the most commonly used method to test for SARS-CoV-2.
COVID-19 Retrospective Studies Female SARS-CoV-2 Humans Machine Learning Male Middle Aged COVID-19 Nucleic Acid Testing Aged Aged, 80 and over Adult Sensitivity and Specificity
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Augmented Human Intelligence and Automated Diagnosis in Flow Cytometry for Hematologic Malignancies.

American journal of clinical pathology Mar 15, 2021
OBJECTIVES: Clinical flow cytometry is laborious, time-consuming, and expensive given the need for data review by highly trained personnel such as technologists and pathologists as well as the significant number of normal cases. Given these issues, a...
Hematologic Neoplasms Diagnosis, Computer-Assisted Flow Cytometry B-Lymphocytes Humans Machine Learning
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