Tootfinder

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
Giuseppe Di Caro, Vahagn Kirakosyan, Alexander G. Abanov, Luca Candelori, Nadine Hartmann, Ernest T. Lam, Kharen Musaelian, Ryan Samson, Dario Villani, Martin T. Wells, Richard J. Wenstrup, Mengjia Xu
https://arxiv.org/abs/2506.03199

Quantum Cognition Machine Learning for Forecasting Chromosomal Instability
The accurate prediction of chromosomal instability from the morphology of circulating tumor cells (CTCs) enables real-time detection of CTCs with high metastatic potential in the context of liquid biopsy diagnostics. However, it presents a significant challenge due to the high dimensionality and complexity of single-cell digital pathology data. Here, we introduce the application of Quantum Cognition Machine Learning (QCML), a quantum-inspired computational framework, to estimate morphology-pred…