976 research outputs found
Current Status and Future Perspectives of Artificial Intelligence in Magnetic Resonance Breast Imaging
No full textRecent advances in artificial intelligence (AI) and deep learning (DL) have impacted many scientific fields including biomedical maging. Magnetic resonance imaging (MRI) is a well-established method in breast imaging with several indications including screening, staging, and therapy monitoring. The rapid development and subsequent implementation of AI into clinical breast MRI has the potential to affect clinical decision-making, guide treatment selection, and improve patient outcomes. The goal of this review is to provide a comprehensive picture of the current status and future perspectives of AI in breast MRI. We will review DL applications and compare them to standard data-driven techniques. We will emphasize the important aspect of developing quantitative imaging biomarkers for precision medicine and the potential of breast MRI and DL in this context. Finally, we will discuss future challenges of DL applications for breast MRI and an AI-augmented clinical decision strategy
: A Methodology and Application Primer
No full textComputer-aided diagnosis (CAD) systems have become an important tool in the assessment of breast tumors with magnetic resonance imaging (MRI). CAD systems can be used for the detection and diagnosis of breast tumors as a "second opinion" review complementing the radiologist's review. CAD systems have many common parts, such as image preprocessing, tumor feature extraction, and data classification that are mostly based on machine-learning (ML) techniques. In this review article, we describe applications of ML-based CAD systems in MRI covering the detection of diagnostically challenging lesions of the breast such as nonmass enhancing (NME) lesions, and furthermore discuss how multiparametric MRI and radiomics can be applied to the study of NME, including prediction of response to neoadjuvant chemotherapy (NAC). Since ML has been widely used in the medical imaging community, we provide an overview about the state-of-the-art and novel techniques applied as classifiers to CAD systems. The differences in the CAD systems in MRI of the breast for several standard and novel applications for NME are explained in detail to provide important examples, illustrating: 1) CAD for detection and diagnosis, 2) CAD in multiparametric imaging, 3) CAD in NAC, and 4) breast cancer radiomics. We aim to provide a comparison between these CAD applications and to illustrate a global view on intelligent CAD systems based on machine and deep learning in MRI of the breast. Level of Evidence 2 Technical Efficacy Stage 2</p
Correction to: Second International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions) (Breast Cancer Research and Treatment, (2019), 174, 2, (279-296), 10.1007/s10549-018-05071-1)
No full textThe article Second International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions), written by Christoph J Rageth, Elizabeth AM O’Flynn, Katja Pinker, Rahel A Kubik-Huch, Alexander Mundinger, Thomas Decker, Christoph Tausch, Florian Dammann, Pascal A. Baltzer, Eva Maria Fallenberg, Maria P Foschini, Sophie Dellas, Michael Knauer, Caroline Malhaire, Martin Sonnenschein, Andreas Boos, Elisabeth Morris, Zsuzsanna Varga, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on November 30, 2018 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on May 30, 2019 to © The Author(s) 2018 and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons.org/licen ses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The original article has been corrected
Measuring Vulnerability to Poverty Using Long-Term Panel Data
No full textMeasuring Vulnerability to Poverty Using Long-Term Panel Data Author & abstract Download & other version 16 References 4 Citations Related works & more Corrections Author Listed: Katja Landau (Georg-August-University Göttingen) Stephan Klasen (Georg-August-University Göttingen) Walter Zucchini (Georg-August-University Göttingen) Registered: Stephan Klasen Abstract We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply di fferent regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty
Resilience as a positive lever: An analysis of sensemaking and meaningful work in the context of organizational change
No full textAuthor Katja SchwarzMasterarbeit Johannes Kepler Universität Linz 2024Arbeit nach Ablauf der Sperre auf den öffentlichen PCs in den Bibliotheken der JKU+Medizin abrufba
Measuring Vulnerability to Poverty Using Long-Term Panel Data
No full textMeasuring Vulnerability to Poverty Using Long-Term Panel Data Author & abstract Download & other version 16 References 4 Citations Related works & more Corrections Author Listed: Katja Landau (Georg-August-University Göttingen) Stephan Klasen (Georg-August-University Göttingen) Walter Zucchini (Georg-August-University Göttingen) Registered: Stephan Klasen Abstract We investigate the accuracy of ex ante assessments of vulnerability to income poverty using cross-sectional data and panel data. We use long-term panel data from Germany and apply di fferent regression models, based on household covariates and previous-year equivalence income, to classify a household as vulnerable or not. Predictive performance is assessed using the Receiver Operating Characteristics (ROC), which takes account of false positive as well as true positive rates. Estimates based on cross-sectional data are much less accurate than those based on panel data, but for Germany, the accuracy of vulnerability predictions is limited even when panel data are used. In part this low accuracy is due to low poverty incidence and high mobility in and out of poverty
Resilience as a positive lever: An analysis of sensemaking and meaningful work in the context of organizational change
No full textAuthor Katja SchwarzMasterarbeit Johannes Kepler Universität Linz 2024Arbeit nach Ablauf der Sperre auf den öffentlichen PCs in den Bibliotheken der JKU+Medizin abrufba
"Meghillàt Estèr". Toward a Transcultural Concept of Religion in Katja Petrowskaja\u27s Novel Vielleicht Esther
No full textIl presente contributo intende rileggere il romanzo Vielleicht Esther (2014) di Katja Petrowskaja proponendo come chiave di lettura la Meghillàt Estèr della Bibbia ebraica. Si vuole dimostrare come, attraverso questo implicito ma preciso riferimento intertestuale, l’autrice affronti nel romanzo anche una riflessione su una possibile transreligione capace di rispecchiare il contesto transculturale contemporaneo.This contribution analyzes Katja Petrowskaja’s novel Vielleicht Esther (2014) by proposing the Megillàt Estèr from the Hebrew Bible as a key interpretative lens. The aim is to demonstrate how, through this subtle yet deliberate intertextual reference, the author weaves into the novel a reflection on the notion of a transreligion, one that resonates with and articulates the complexities of our contemporary transcultural landscape
Casanovas are liars : behavioral syndromes, sperm competition risk, and the evolution of deceptive male mating behavior in live-bearing fishes [version 2; referees: 2 approved, 1 approved with reservations]
No full textMale reproductive biology can by characterized through competition over mates as well as mate choice. Multiple mating and male mate choice copying, especially in internally fertilizing species, set the stage for increased sperm competition, i.e., sperm of two or more males can compete for fertilization of the female’s ova. In the internally fertilizing fish Poecilia mexicana, males respond to the presence of rivals with reduced expression of mating preferences (audience effect), thereby lowering the risk of by-standing rivals copying their mate choice. Also, males interact initially more with a non-preferred female when observed by a rival, which has been interpreted in previous studies as a strategy to mislead rivals, again reducing sperm competition risk (SCR). Nevertheless, species might differ consistently in their expression of aggressive and reproductive behaviors, possibly due to varying levels of SCR. In the current study, we present a unique data set comprising ten poeciliid species (in two cases including multiple populations) and ask whether species can be characterized through consistent differences in the expression of aggression, sexual activity and changes in mate choice under increased SCR. We found consistent species-specific differences in aggressive behavior, sexual activity as well as in the level of misleading behavior, while decreased preference expression under increased SCR was a general feature of all but one species examined. Furthermore, mean sexual activity correlated positively with the occurrence of potentially misleading behavior. An alternative explanation for audience effects would be that males attempt to avoid aggressive encounters, which would predict stronger audience effects in more aggressive species. We demonstrate a positive correlation between mean aggressiveness and sexual activity (suggesting a hormonal link as a mechanistic explanation), but did not detect a correlation between aggressiveness and audience effects. Suites of correlated behavioral tendencies are termed behavioral syndromes, and our present study provides correlational evidence for the evolutionary significance of SCR in shaping a behavioral syndrome at the species level across poeciliid taxa
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