Peripheral blood cell diagnostics

AI-Driven Peripheral Blood Cell Diagnostics & Advanced Anemia Screening

AimaLabs is a medical technology start-up dedicated to the digital transformation of hematology. We utilize advanced computer vision and deep learning to automate the identification and classification of peripheral blood cells. Our platform is designed to bridge the gap between traditional manual microscopy and the need for scalable, objective data in modern clinical research.

Core Capabilities & Technical Value

• Comprehensive Cell Phenotyping: Our AI replaces subjective manual counting with automated classification of leukocytes, platelets, and erythrocytes. This ensures diagnostic consistency across different clinical sites, which is a critical requirement for Horizon Europe multi-center studies.

• Advanced Anemia Screening: We specialize in the automated morphological analysis of red blood cells (RBCs). By identifying variations in cell size, shape, and color, our technology supports the early detection and differential diagnosis of various anemias (such as iron deficiency or microcytic anemia), providing a rapid screening layer for large patient cohorts.

• High-Resolution Morphological Insights: The platform captures and analyzes subtle morphological shifts in the blood film that may be overlooked during routine manual reviews. This provides a more granular view of a patient’s hematological profile than standard automated counters.

• Standardized Digital Integration: AimaLabs provides objective, reproducible data outputs. This aligns with the EU’s goals for Digital Health and the creation of harmonized health data spaces for European research.

Synergistic Goals for Horizon Europe Clusters

We are seeking to cooperate with consortium partners—ranging from clinical trial leads to biotech researchers—to:

1. Optimize Clinical Workflows: Act as the digital pathology partner to provide real-time, objective blood cell data for longitudinal patient monitoring.

2. Support Population Health Initiatives: Deploy our AI-powered anemia screening tools to assist in large-scale public health studies and chronic disease management programs.

3. Data-Driven Research: Combine our morphological AI data with other multi-omic layers (such as genomics or proteomics) provided by cluster partners to uncover new clinical correlations.