output
20152026
most citedClassification supporting COVID-19 diagnostics based on patient survey data

6 citations

5 papers

cs.CV2026

Can Unsupervised Methods Outperform Supervised Deep Learning When Ground Truth Is Sparse? A Case Study of Bronchovascular Bundle Segmentation in Low-Dose CT

Anna Mrukwa, Marek Socha, Aleksandra Suwalska +9

Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an early screening stage. However,…

eess.IV2024★ 1 cited

Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography

Przemysław Bombiński, Patryk Szatkowski, Bartłomiej Sobieski +6

Lung mask creation lacks well-defined criteria and standardized guidelines, leading to a high degree of subjectivity between annotators. In this study, we assess the underestimatio…

eess.IV2022★ 1 cited

CIRCA: comprehensible online system in support of chest X-rays-based COVID-19 diagnosis

Wojciech Prazuch, Aleksandra Suwalska, Marek Socha +19

Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learn…

cs.LG2020★ 6 cited

Classification supporting COVID-19 diagnostics based on patient survey data

Joanna Henzel, Joanna Tobiasz, Michał Kozielski +11

Distinguishing COVID-19 from other flu-like illnesses can be difficult due to ambiguous symptoms and still an initial experience of doctors. Whereas, it is crucial to filter out th…

q-bio.CB2015

Effective diffusion rates and cross-correlation analysis of "acid growth" data

Mariusz Pietruszka, Aleksandra Haduch-Sendecka

We investigated the growth-temperature relationship in plants using a quantitative perspective of a recently derived growth functional. We showed that auxin-induced growth is achie…