multi-class-classification

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topic2 events

papersSEP 12 04:00 UTC

Instance segmentation models support automated multi-class wound assessment

A new arXiv paper presents an approach to automated wound care that combines dedicated instance segmentation models for detecting wound boundaries with multi-class classification. The authors argue that existing AI systems for wound analysis tend to be narrow in scope, and propose handling boundary detection and wound typing as separate, specialized tasks. The method targets clinical decision support in both chronic and acute wound management.

medical-imaging/segmentation/computer-vision/healthcare

papersSEP 10 04:00 UTC

Multi-label vs multi-class classification of blood cells in microfluidic channels

A new study examines how to classify blood cells and their aggregates imaged by deformability cytometry, a high-throughput imaging flow cytometry technique that measures cellular stiffness alongside properties like area and elongation. The researchers compare multi-label and multi-class machine learning approaches for identifying individual cells and clusters within microfluidic channels. The work aims to determine which labeling scheme better captures cases where multiple cell types or aggregates appear in a single measurement.

machine-learning/classification/imaging/healthcare