AIMC Topic: Automation

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Robotic Automation of In Vivo Two-Photon Targeted Whole-Cell Patch-Clamp Electrophysiology.

Neuron
Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed "blind," meaning that throughput for sa...

Screening Electronic Health Record-Related Patient Safety Reports Using Machine Learning.

Journal of patient safety
INTRODUCTION: The objective of this study was to develop a semiautomated approach to screening cases that describe hazards associated with the electronic health record (EHR) from a mandatory, population-based patient safety reporting system.

Smart management of sample dilution using an artificial neural network to achieve streamlined processes and saving resources: the automated nephelometric testing of serum free light chain as case study.

Clinical chemistry and laboratory medicine
BACKGROUND: Saving resources is a paramount issue for the modern laboratory, and new trainable as well as smart technologies can be used to allow the automated instrumentation to manage samples more efficiently in order to achieve streamlined process...

Automated Classification of Multi-Labeled Patient Safety Reports: A Shift from Quantity to Quality Measure.

Studies in health technology and informatics
Over the past two decades, there have seen an ever-increasing amount of patient safety reports yet the capacity of extracting useful information from the reports remains limited. Classification of patient safety reports is the first step of performin...

Summarizing an Ontology: A "Big Knowledge" Coverage Approach.

Studies in health technology and informatics
Maintenance and use of a large ontology, consisting of thousands of knowledge assertions, are hampered by its scope and complexity. It is important to provide tools for summarization of ontology content in order to facilitate user "big picture" compr...

Development of a Deep Learning Algorithm for Automatic Diagnosis of Diabetic Retinopathy.

Studies in health technology and informatics
This paper mainly focuses on the deep learning application in classifying the stage of diabetic retinopathy and detecting the laterality of the eye using funduscopic images. Diabetic retinopathy is a chronic, progressive, sight-threatening disease of...