AIMC Topic: Automation, Laboratory

Clear Filters Showing 51 to 60 of 100 articles

Automated System for Small-Population Single-Particle Processing Enabled by Exclusive Liquid Repellency.

SLAS technology
Exclusive liquid repellency (ELR) describes an extreme wettability phenomenon in which a liquid phase droplet is completely repelled from a solid phase when exposed to a secondary immiscible liquid phase. Earlier, we developed a multi-liquid-phase op...

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies.

Virchows Archiv : an international journal of pathology
Histopathologic grading of prostate cancer using Gleason patterns (GPs) is subject to a large inter-observer variability, which may result in suboptimal treatment of patients. With the introduction of digitization and whole-slide images of prostate b...

Machine learning algorithms for the detection of spurious white blood cell differentials due to erythrocyte lysis resistance.

Journal of clinical pathology
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...

Rapid histology of laryngeal squamous cell carcinoma with deep-learning based stimulated Raman scattering microscopy.

Theranostics
Maximal resection of tumor while preserving the adjacent healthy tissue is particularly important for larynx surgery, hence precise and rapid intraoperative histology of laryngeal tissue is crucial for providing optimal surgical outcomes. We hypothes...

Automation and artificial intelligence in the clinical laboratory.

Critical reviews in clinical laboratory sciences
The daily operation of clinical laboratories will be drastically impacted by two disruptive technologies: automation and artificial intelligence (the development and use of computer systems able to perform tasks that normally require human intelligen...

Automated Analytical Measurement Processes Using a Dual-Arm Robotic System.

SLAS technology
The demand for automation in the analytical laboratory is high. In contrast to well-automated bioscreening and high-throughput and high-content screening processes, analytical measurement procedures are complex in their structure and changing frequen...

Streamlining Quality Review of Mass Spectrometry Data in the Clinical Laboratory by Use of Machine Learning.

Archives of pathology & laboratory medicine
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.

Standardizing Automated DNA Assembly: Best Practices, Metrics, and Protocols Using Robots.

SLAS technology
The advancement of synthetic biology requires the ability to create new DNA sequences to produce unique behaviors in biological systems. Automation is increasingly employed to carry out well-established assembly methods of DNA fragments in a multiple...

High-Quality Immunohistochemical Stains Through Computational Assay Parameter Optimization.

IEEE transactions on bio-medical engineering
Accurate profiling of tumors using immunohistochemistry (IHC) is essential in cancer diagnosis. The inferences drawn from IHC-stained images depend to a great extent on the quality of immunostaining, which is in turn affected strongly by assay parame...