The Role of AI Assistance in Conventional Karyotyping: Enhancements, Limitations, and the Continuing Need for Human Expertise
This clinical study evaluates the performance of ASI’s computer-aided karyotyping software in routine chromosome analysis, demonstrating substantial improvements in chromosome placement accuracy and workflow efficiency while reinforcing the essential role of expert cytogeneticists in diagnostic interpretation.
ASI’s New Software Release | V8.4.2
GenASIs version 8.4.2 introduces powerful new features that streamline laboratory workflows, combining computer-aided cytogenetics, integrated pathology capabilities, and enhanced cybersecurity in a single platform.
Use of Artificial Intelligence to enhance karyotyping efficiency of both normal and abnormal metaphases of different resolutions – a first Australian experience
The results show a four-fold improvement in chromosome classification accuracy and a 52% reduction in analysis time, highlighting the value of AI-assisted karyotyping for routine and complex cytogenetic workflows.
Ruling out of Fanconi Anemia in children with bone marrow failure, important but not always easy – a case report
The findings demonstrate how integrated cytogenetic, genetic, and functional analyses can support accurate diagnosis, helping to rule out Fanconi Anemia and guide appropriate clinical management in complex cases.
Multimodal Cytogenetic and Molecular Approach for the Detection of a Constitutional Balanced Paracentric Inversion Disrupting RB1 in an Infant
A recent study highlights the importance of multimodal cytogenetic and molecular approaches in detecting complex structural variants.
Integrated Workflow for the Digital Review of FISH Images in the Laboratory Image Management System
Results show over 99% correlation between dedicated FISH analysis and IMS review, supporting reliable integration of FISH images into digital pathology workflows.
Digital Linked Visualization of H&E and Immunofluorescence WSI in Dermatopathology – a Pilot Evaluation
The study demonstrates high concordance between digital and manual assessments, highlighting the potential of combined H&E and IF WSI review to improve diagnostic insight and efficiency.
Multicenter pilot evaluation of a new AI-based metaphase finder for application in karyotyping peripheral blood and bone marrow specimens
This multicenter pilot study assesses a new AI-based metaphase finder designed to improve detection during slide scanning. The results demonstrate increased metaphase identification and reduced capture of non-metaphase material, enhancing efficiency in karyotyping workflows.
Comparative evaluation of an AI-based scanner-agnostic add-on utility versus conventional karyotyping software
This study evaluates an AI-based scanner-agnostic add-on for automated karyotyping that integrates with existing imaging systems. Results show a significant reduction in metaphase analysis time, supporting faster and more efficient cytogenetic workflows.
Automated Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Carcinoma Using Deep Learning on Pretreatment Core Needle Biopsy Samples
A new breast cancer study demonstrates how ASI’s HiPath Pro platform support AI-driven predictive oncology through high-quality digital pathology imaging.
Agreement analysis between manual and computational scoring of Ki-67 in breast cancer
ASI’s second abstract presented at ECP 2025 demonstrates strong agreement between manual and computational scoring of Ki-67 in breast cancer. The study validates ASI’s AI-powered quantification tools as a reliable complement to routine pathology assessment.
Computer-aided scoring as an objective method in the assessment of HER2 immunostaining in breast cancer with high intra-tumoral heterogeneity
This study shows that computer-aided scoring provides a reliable and reproducible method for assessing HER2 immunostaining in breast cancer with high intra-tumoral heterogeneity.