1 citations · 1 across the 2 of their papers we have counts for
4 papers
Quantitative characterization of superconducting qubits as particle detectors
Francesco De Dominicis, Raja Yasir Mehmood Khan, Dounia L Helis +22
Ionizing radiation is a major source of correlated errors in superconducting quantum processors, yet the mechanisms responsible for the qubit response to particle interactions rema…
Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers
Vivek Singh, Shikha Chaganti, Matthias Siebert +6
Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy po…
Evaluating radiation impact on transmon qubits in above and underground facilities
Francesco De Dominicis, Tanay Roy, Ambra Mariani +20
Superconducting qubits can be sensitive to abrupt energy deposits caused by cosmic rays and ambient radioactivity. While previous studies have explored correlated effects in time a…
Deep Neural Networks for ECG-free Cardiac Phase and End-Diastolic Frame Detection on Coronary Angiographies
Costin Ciusdel, Alexandru Turcea, Andrei Puiu +10
Invasive coronary angiography (ICA) is the gold standard in Coronary Artery Disease (CAD) imaging. Detection of the end-diastolic frame (EDF) and, in general, cardiac phase detecti…