Search Results - "Zigutyte, Laura"

Artificial intelligence in liver cancer — new tools for research and patient management by Calderaro, Julien, Žigutytė, Laura, Truhn, Daniel, Jaffe, Ariel, Kather, Jakob Nikolas

“…Liver cancer has high incidence and mortality globally. Artificial intelligence (AI) has advanced rapidly, influencing cancer care. AI systems are already…”
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Reconstruction of patient-specific confounders in AI-based radiologic image interpretation using generative pretraining by Han, Tianyu, Žigutytė, Laura, Huck, Luisa, Huppertz, Marc Sebastian, Siepmann, Robert, Gandelsman, Yossi, Blüthgen, Christian, Khader, Firas, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob Nikolas, Truhn, Daniel

“…Reliably detecting potentially misleading patterns in automated diagnostic assistance systems, such as those powered by artificial intelligence (AI), is…”
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Using histopathology latent diffusion models as privacy-preserving dataset augmenters improves downstream classification performance by Niehues, Jan M., Müller-Franzes, Gustav, Schirris, Yoni, Wagner, Sophia Janine, Jendrusch, Michael, Kloor, Matthias, Pearson, Alexander T., Muti, Hannah Sophie, Hewitt, Katherine J., Veldhuizen, Gregory P., Zigutyte, Laura, Truhn, Daniel, Kather, Jakob Nikolas

“…Latent diffusion models (LDMs) have emerged as a state-of-the-art image generation method, outperforming previous Generative Adversarial Networks (GANs) in…”
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FRI-499-YI Counterfactual explanations for histopathology slides of hepatocellular carcinoma and cholangiocarcinoma enhance the understanding of artificial intelligence models by Žigutytė, Laura, Hewitt, Katherine, Kather, Jakob Nikolas

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Use of artificial intelligence for liver diseases: A survey from the EASL congress 2024 by Žigutytė, Laura, Sorz-Nechay, Thomas, Clusmann, Jan, Kather, Jakob Nikolas

“…Artificial intelligence (AI) methods enable humans to analyse large amounts of data, which would otherwise not be feasibly quantifiable. This is especially…”
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Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative Pretraining by Han, Tianyu, Žigutytė, Laura, Huck, Luisa, Huppertz, Marc, Siepmann, Robert, Gandelsman, Yossi, Blüthgen, Christian, Khader, Firas, Kuhl, Christiane, Nebelung, Sven, Kather, Jakob, Truhn, Daniel

“…Detecting misleading patterns in automated diagnostic assistance systems, such as those powered by Artificial Intelligence, is critical to ensuring their…”
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