3 papers
cs.LG2026
Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors
Vojtěch Novák, Ivan Zelinka, Lenka Přibylová +3
This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analyzing clinical data with 14\%…
quant-ph2025
Quantum Machine Learning for Predicting Anastomotic Leak: A Clinical Study
Vojtěch Novák, Ivan Zelinka, Lenka Přibylová +2
Anastomotic leak (AL) is a life-threatening complication following colorectal surgery, and its accurate prediction remains a significant clinical challenge. This study explores the…
quant-ph2025
Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies
Vojtěch Novák, Ivan Zelinka, Lenka Přibylová +1
This study investigates the application of quantum neural networks (QNNs) for propensity score estimation to address selection bias in comparing survival outcomes between laparosco…