1 citations · 1 across the 3 of their papers we have counts for
7 papers
Data complexity signature predicts quantum projected learning benefit for antibiotic resistance
Kahn Rhrissorrakrai, Filippo Utro, Alex Milinovich +4
This study presents the first large-scale empirical evaluation of quantum machine learning for predicting antibiotic resistance in clinical urine cultures. Antibiotic resistance is…
Enhanced Prediction of CAR T-Cell Cytotoxicity with Quantum-Kernel Methods
Filippo Utro, Meltem Tolunay, Kahn Rhrissorrakrai +6
Chimeric antigen receptor (CAR) T-cells are T-cells engineered to recognize and kill specific tumor cells. Through their extracellular domains, CAR T-cells bind tumor cell antigens…
Quantum Ensembling Methods for Healthcare and Life Science
Kahn Rhrissorrakrai, Kathleen E. Hamilton, Prerana Bangalore Parthsarathy +4
Learning on small data is a challenge frequently encountered in many real-world applications. In this work we study how effective quantum ensemble models are when trained on small…
On Quantum Random Walks in Biomolecular Networks
Viacheslav Dubovitskii, Aritra Bose, Filippo Utro +1
Biomolecular networks, such as protein-protein interactions, gene-gene associations, and cell-cell interactions, offer valuable insights into the complex organization of biological…
Quantum machine learning framework for longitudinal biomedical studies
Maria Demidik, Filippo Utro, Alexey Galda +3
Longitudinal biomedical studies play a vital role in tracking disease progression, treatment response, and the emergence of resistance mechanisms, particularly in complex disorders…
Bounds on the realizations of zero-nonzero patterns and sign conditions of polynomials restricted to varieties and applications
Saugata Basu, Laxmi Parida
We obtain upper bounds, independent of the ambient dimension, for the number of realizable zero-nonzero patterns and (over ordered fields) sign conditions of a finite family of pol…