AIMC Topic: Automation, Laboratory

Clear Filters Showing 11 to 20 of 97 articles

Concept of flexible no-code automation for complex sample preparation procedures.

Journal of chromatography. A
Driven by demographic changes and dwindling Science Technology Engineering Mathematics enrolments, our research introduces no-code automation as a strategic response, aimed at mitigating labor shortages while enhancing productivity and safety in the ...

Deep integration of low-cost liquid handling robots in an industrial pharmaceutical development environment.

SLAS technology
The pharmaceutical industry is increasingly embracing laboratory automation to enhance experimental efficiency and operational resilience, particularly through the integration of automated liquid handlers (ALHs). This paper explores the integration o...

Improvement of bioanalytical parameters through automation: suitability of a hand-like robotic system.

Analytical and bioanalytical chemistry
Commercial automation systems for small- and medium-sized laboratories, including research environments, are often complex to use. For liquid handling systems (LHS), development is required not only for the robot's movements but also for adapting the...

Towards robotic laboratory automation plug & play: Reference architecture model for robot integration.

SLAS technology
Supportive robotic solutions take over mundane, but essential tasks from human workforce in biomedical research and development laboratories. The newest technologies in collaborative and mobile robotics enable the utilization in the human-centered an...

Combining Artificial Intelligence and Simplified Image Processing for the Automatic Detection of Mycobacterium tuberculosis in Acid-fast Stain : A Cross-institute Training and Validation Study.

The American journal of surgical pathology
Tuberculosis (TB) poses a significant health threat in Taiwan, necessitating efficient detection methods. Traditional screening for acid-fast positive bacilli in acid-fast stain is time-consuming and prone to human error due to staining artifacts. To...

Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.

Journal of clinical microbiology
In clinical bacteriology laboratories, reading and processing of sterile plates remain a significant part of the routine workload (30%-40% of the plates). Here, an algorithm was developed for bacterial growth detection starting with any type of speci...

FocA: A deep learning tool for reliable, near-real-time imaging focus analysis in automated cell assay pipelines.

SLAS discovery : advancing life sciences R & D
The increasing use of automation in cellular assays and cell culture presents significant opportunities to enhance the scale and throughput of imaging assays, but to do so, reliable data quality and consistency are critical. Realizing the full potent...

Laboratory automation, informatics, and artificial intelligence: current and future perspectives in clinical microbiology.

Frontiers in cellular and infection microbiology
Clinical diagnostic laboratories produce one product-information-and for this to be valuable, the information must be clinically relevant, accurate, and timely. Although diagnostic information can clearly improve patient outcomes and decrease healthc...

Towards robotic laboratory automation Plug & play: Survey and concept proposal on teaching-free robot integration with the lapp digital twin.

SLAS technology
The Laboratory Automation Plug & Play (LAPP) framework is an over-arching reference architecture concept for the integration of robots in life science laboratories. The plug & play nature lies in the fact that manual configuration is not required, in...