The Emergence of Artificial Intelligence-Guided Karyotyping: A Review and Reflection
This recent review by Wake Forest University School of Medicine explores the emergence of AI-guided karyotyping, featuring ASI’s HiBand system as a leading example.
Explore Cutting-Edge ASI Clinical Studies
This recent review by Wake Forest University School of Medicine explores the emergence of AI-guided karyotyping, featuring ASI’s HiBand system as a leading example.
ASI enhances interoperability in chromosome analysis, enabling AI-powered karyotyping without replacing existing imaging systems. Our latest study demonstrates the seamless import of third-party scanned metaphases into ASI’s platform, automating karyogram generation and optimizing analysis efficiency.
ASI’s AI-powered karyotyping technology enhances efficiency in cytogenetics labs by significantly reducing analysis time. Our latest study demonstrates a 53% reduction in karyotyping time for peripheral blood samples using AI-based automation, improving accuracy and streamlining workflows.
A recent study published by Dr. Lui Ng and Colleagues highlights the use of digital image analysis for assessing prognostic biomarkers like CDH17 in colorectal cancer (CRC).
Detecting genetic abnormalities in cancer, crucial for diagnosis and treatment, often uses fluorescence in-situ hybridization (FISH). Automated slide scanners enhance FISH analysis by reducing microscope bottlenecks, improving accuracy, and enabling remote reviews.
This in-depth review highlights groundbreaking research in genetic studies across multiple species, utilizing both brightfield and FISH imaging techniques.
The Aided Karyotyping method significantly reduces the time needed to correct and analyze each karyogram by half.
The AON Central Lab is recognized as the first laboratory in the world to use this technology,
which decreases analysis time.
HER2 IHC scoring in new method that integrates manual interpretation with computer-aided quantitative analysis, setting a new standard in diagnostic precision.
Interoperability in digital FISH enumeration allows to use regions of interest marked by the pathologist on the H&E or IHC image when requesting FISH.