AIMC Topic: Laboratories

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Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic is probably the greatest health catastrophe of the modern era. Spain's health care system has been exposed to uncontrollable numbers of patients over a short period, causing the system to collapse. Given that diagnos...

Uncertainty-Aware Blind Image Quality Assessment in the Laboratory and Wild.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Performance of blind image quality assessment (BIQA) models has been significantly boosted by end-to-end optimization of feature engineering and quality regression. Nevertheless, due to the distributional shift between images simulated in the laborat...

Establishing Classifiers With Clinical Laboratory Indicators to Distinguish COVID-19 From Community-Acquired Pneumonia: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: The initial symptoms of patients with COVID-19 are very much like those of patients with community-acquired pneumonia (CAP); it is difficult to distinguish COVID-19 from CAP with clinical symptoms and imaging examination.

Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study.

Journal of medical Internet research
BACKGROUND: Conventional diagnosis of COVID-19 with reverse transcription polymerase chain reaction (RT-PCR) testing (hereafter, PCR) is associated with prolonged time to diagnosis and significant costs to run the test. The SARS-CoV-2 virus might lea...

Integrating Mobile Robots into Automated Laboratory Processes: A Suitable Workflow Management System.

SLAS technology
The general trend of automation is currently increasing in life science laboratories. The samples to be examined show a high diversity in their structures and composition as well as the determination methods. Complex automation lines such as those us...

Unlocking the efficiency of genomics laboratories with robotic liquid-handling.

BMC genomics
In research and clinical genomics laboratories today, sample preparation is the bottleneck of experiments, particularly when it comes to high-throughput next generation sequencing (NGS). More genomics laboratories are now considering liquid-handling ...

A deep learning solution to recommend laboratory reduction strategies in ICU.

International journal of medical informatics
OBJECTIVE: To build a machine-learning model that predicts laboratory test results and provides a promising lab test reduction strategy, using spatial-temporal correlations.

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Drug and alcohol dependence
BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampli...

Collaborative AI and Laboratory Medicine integration in precision cardiovascular medicine.

Clinica chimica acta; international journal of clinical chemistry
Artificial Intelligence (AI) is a broad term that combines computation with sophisticated mathematical models and in turn allows the development of complex algorithms which are capable to simulate human intelligence such as problem solving and learni...

Computer Vision and Artificial Intelligence Are Emerging Diagnostic Tools for the Clinical Microbiologist.

Journal of clinical microbiology
Artificial intelligence (AI) is increasingly becoming an important component of clinical microbiology informatics. Researchers, microbiologists, laboratorians, and diagnosticians are interested in AI-based testing because these solutions have the pot...