AIMC Topic: Clinical Laboratory Techniques
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Streamlining Quality Review of Mass Spectrometry Data in the Clinical Laboratory by Use of Machine Learning.
Archives of pathology & laboratory medicine
Feb 20, 2019
CONTEXT.—: Turnaround time and productivity of clinical mass spectrometric (MS) testing are hampered by time-consuming manual review of the analytical quality of MS data before release of patient results.
Artificial Neural Network for Total Laboratory Automation to Improve the Management of Sample Dilution.
SLAS technology
Jul 10, 2016
Diluting a sample to obtain a measure within the analytical range is a common task in clinical laboratories. However, for urgent samples, it can cause delays in test reporting, which can put patients' safety at risk. The aim of this work is to show a...
An unsupervised learning method to identify reference intervals from a clinical database.
Journal of biomedical informatics
Dec 19, 2015
Reference intervals are critical for the interpretation of laboratory results. The development of reference intervals using traditional methods is time consuming and costly. An alternative approach, known as an a posteriori method, requires an expert...
Multi-Dimensional Laboratory Test Score as a Proxy for Health.
Studies in health technology and informatics
May 25, 2022
The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Dif...
The emergence of new trends in clinical laboratory diagnosis.
Saudi medical journal
Nov 1, 2020
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of diseases. Computational approaches are being increasingly used for more precise diagnosis of the clinical p...
Deus Ex Machina? Predicting SARS-CoV-2 Infection from Lab Tests Using Machine Learning.
Clinical chemistry
Nov 1, 2020
Humans
Machine Learning
Pandemics
COVID-19
Reverse Transcriptase Polymerase Chain Reaction
Coronavirus Infections
COVID-19 Testing
Programming Languages
Algorithms
Electronic Health Records
SARS-CoV-2
Clinical Laboratory Techniques
Betacoronavirus
Pneumonia, Viral
Laboratories
Probability
Blood Cell Count
Routine Laboratory Blood Tests Predict SARS-CoV-2 Infection Using Machine Learning.
Clinical chemistry
Nov 1, 2020
BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PC...
Reverse Transcriptase Polymerase Chain Reaction
ROC Curve
Models, Theoretical
Coronavirus Infections
Adult
Male
Middle Aged
Pneumonia, Viral
COVID-19 Testing
Laboratories
Hematologic Tests
Clinical Laboratory Techniques
Machine Learning
Retrospective Studies
Humans
Pandemics
Female
COVID-19
Aged
Young Adult
An artificial intelligence approach to COVID-19 infection risk assessment in virtual visits: A case report.
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2020
OBJECTIVE: In an effort to improve the efficiency of computer algorithms applied to screening for coronavirus disease 2019 (COVID-19) testing, we used natural language processing and artificial intelligence-based methods with unstructured patient dat...
Pneumonia, Viral
Algorithms
Electronic Health Records
SARS-CoV-2
Organizational Case Studies
Risk Assessment
Neural Networks, Computer
Clinical Laboratory Techniques
Deep Learning
Humans
Artificial Intelligence
South Carolina
ROC Curve
Betacoronavirus
Pandemics
Natural Language Processing
Coronavirus Infections
COVID-19
Telemedicine
COVID-19 Testing
Using a simple open-source automated machine learning algorithm to forecast COVID-19 spread: A modelling study.
Advances in respiratory medicine
Jan 1, 2020
INTRODUCTION: Machine learning algorithms have been used to develop prediction models in various infectious and non-infectious settings including interpretation of images in predicting the outcome of diseases. We demonstrate the application of one su...
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