3 results match your criteria: "Tu Wien University[Affiliation]"

The automated extraction of critical information from electronic medical records, such as oncological medical events, has become increasingly important with the widespread use of electronic health records. However, extracting tumor-related medical events can be challenging due to their unique characteristics. To address this difficulty, we propose a novel approach that utilizes Generative Adversarial Networks (GANs) for data augmentation and pseudo-data generation algorithms to improve the model's transfer learning skills for various tumor-related medical events.

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Radionuclide metrology methods and analysis of the Joint Danube Survey 4 sediment samples.

Appl Radiat Isot

June 2023

Labor für Strahlenschutz, Magistratsabteilung 39, Stadt Wien, Währinger Gürtel 18-20, 1190, Wien, Austria.

This low-level radionuclide metrology research work was carried out within the Joint Danube Survey 4 (JDS4), coordinated in 2018-2020 by the International Commission for the Protection of the Danube River (ICPDR). The gamma-emitting radionuclides of the sediment samples were analysed by low-level gamma-ray spectrometry. The activity concentration of Sr was determined by liquid scintillation counting (LSC) after isolating the radio-strontium using a new radiochemical separation method.

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Lung cancer is a leading cause of cancer-related deaths globally. Early detection is crucial for improving patient survival rates. Deep learning (DL) has shown promise in the medical field, but its accuracy must be evaluated, particularly in the context of lung cancer classification.

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