Georg Dorffner

Georg Dorffner
Medical University of Vienna | MedUni Vienna · Section for Artificial Intelligence

PhD

About

316
Publications
51,026
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6,143
Citations
Additional affiliations
January 1988 - December 2007
Austrian Research Institute for Artificial Intelligence
Position
  • Head of Research Group
January 1987 - present
Medical University of Vienna
Position
  • Professor (Associate)

Publications

Publications (316)
Article
With the advent of digital pathology and microscopic systems that can scan and save whole slide histological images automatically, there is a growing trend to use computerized methods to analyze acquired images. Among different histopathological image analysis tasks, nuclei instance segmentation plays a fundamental role in a wide range of clinical...
Article
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Purpose The public medical universities in Austria (educating 11,000 students) developed a joint public distance learning series in which clinicians discussed current digital lighthouse projects in their specialty. This study aims to examine the changes in attitude and knowledge of the participants before and after the lecture series to gain insigh...
Preprint
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Objectives Risk-reducing surgeries are common in patients with breast cancer gene (BRCA) mutations. Certain patients develop breast cancer before they opt for these surgeries. We aimed to examine the frequency of risk-reducing mastectomies and salpingo-oophorectomy among Austrian patients with breast cancer and BRCA mutations. Methods In 2014, we...
Article
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In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior segmentation performances compared to classical machine learning and image processing techniques. How...
Preprint
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Objectives Risk-reducing surgeries are common in patients with breast cancer gene (BRCA) mutations. Certain patients develop breast cancer before they opt for these surgeries. We examined the frequency of risk-reducing mastectomies and salpingo-oophorectomy among Austrian patients with breast cancer and BRCA mutations. Methods In 2014, we establis...
Preprint
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In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for this task, supervised deep learning (DL) methods have shown superior segmentation performances compared to classical machine learning and image processing techniques. How...
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Background Liver metastases are common in patients with breast cancer, and determining the factors associated with such metastases may improve both their early detection and treatment. Given that liver function protein level changes in these patients have not been determined, the aim of our study was to investigate liver function protein level chan...
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Evidence theory by Dempster-Shafer for determination of hormone receptor status in breast cancer samples was introduced in our previous paper. One major topic pointed out here is the link between pieces of evidence found from different origins. In this paper the challenge of selecting appropriate ways of fusing evidence, depending on the type and q...
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Even in the era of precision medicine, with various molecular tests based on omics technologies available to improve the diagnosis process, microscopic analysis of images derived from stained tissue sections remains crucial for diagnostic and treatment decisions. Among other cellular features, both nuclei number and shape provide essential diagnost...
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Digitalisation is changing all areas of our daily life. This changing environment requires new competences from physicians in all specialities. This study systematically surveyed the knowledge, attitude, and interests of medical students. These results will help further develop the medical curriculum, as well as increase our understanding of future...
Article
Computational sleep scoring from multimodal neurophysiological time-series (polysomnography PSG) has achieved impressive clinical success. Models that use only a single electroencephalographic (EEG) channel from PSG have not yet received the same clinical recognition, since they lack Rapid Eye Movement (REM) scoring quality. The question whether th...
Preprint
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Measuring the performance of natural language processing models is challenging. Traditionally used metrics, such as BLEU and ROUGE, originally devised for machine translation and summarization, have been shown to suffer from low correlation with human judgment and a lack of transferability to other tasks and languages. In the past 15 years, a wide...
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Objectives: The retinoblastoma (RB) pathway is crucial in the development and progression of many cancers. To better understand the biology of progressive breast cancer (BC), we examined protein expression of the RB pathway in primary BCs and matched axillary lymph node metastases (LM). Methods: Immunohistochemistry was used to evaluate cyclin D...
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Background: The rationale of a postulated decrease in fertility rate development is still being debated. Among the multiple influencing factors, socioeconomic variables and their complex influence are of particular interest. Methods: Data on socioeconomic and health variables from 1976-2014 of 30 countries within the OECD region were analysed fo...
Preprint
BACKGROUND Digitalisation is changing all areas of our daily life. With COVID-19, digital health received an additional boost in the medical area. The usage of telemedicine applications increased by 70% in 2020. The prediction for artificial intelligence (AI) applications shows a sharp increase over the next few years. This changing environment req...
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Background While machine learning (ML) algorithms may predict cardiovascular outcomes more accurately than statistical models, their result is usually not representable by a transparent formula. Hence, it is often unclear how specific values of predictors lead to the predictions. We aimed to demonstrate with graphical tools how predictor-risk relat...
Chapter
Complex sleep stage transition rules pose a challenge for the learning of inter-epoch context with Deep Neural Networks (DNNs) in ElectroEncephaloGraphy (EEG) based sleep scoring. While DNNs were able to overcome the limits of expert systems, the dominant bidirectional Long Short-Term Memory (LSTM) still has some limitations of Recurrent Neural Net...
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Aims: We tested the hypothesis that artificial intelligence (AI)-powered algorithms applied to cardiac magnetic resonance (CMR) images could be able to detect the potential patterns of cardiac amyloidosis (CA). Readers in CMR centers with a low volume of referrals for the detection of myocardial storage diseases or a low volume of CMRs, in general...
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Background Diagnosis of cardiac amyloidosis (CA) requires advanced imaging techniques. Typical surface ECG patterns have been described, but their diagnostic abilities are limited. Objective The aim was to perform a thorough electrophysiological characterisation of patients with CA and derive an easy-to-use tool for diagnosis. Methods We applied...
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Background The diagnosis of cardiac amyloidosis (CA) requires advanced imaging techniques. Typical surface ECG patterns have been described, but their diagnostic value is limited. Purpose The aim of this study was to perform a comprehensive electrophysiological characterization in CA patients and to develop a robust, easy-to-use diagnostic tool....
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Purpose State‐of‐the‐art whole‐brain MRSI with spatial‐spectral encoding and multichannel acquisition generates huge amounts of data, which must be efficiently processed to stay within reasonable reconstruction times. Although coil combination significantly reduces the amount of data, currently it is performed in image space at the end of the recon...
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Nuclei instance segmentation can be considered as a key point in the computer-mediated analysis of histological fluorescence-stained (FS) images. Many computer-assisted approaches have been proposed for this task, and among them, supervised deep learning (DL) methods deliver the best performances. An important criterion that can affect the DL-based...
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Nuclei instance segmentation plays an important role in the analysis of hematoxylin and eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to train these models. There are two main types of tissue processing protoc...
Preprint
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Nuclei instance segmentation plays an important role in the analysis of Hematoxylin and Eosin (H&E)-stained images. While supervised deep learning (DL)-based approaches represent the state-of-the-art in automatic nuclei instance segmentation, annotated datasets are required to train these models. There are two main types of tissue processing protoc...
Preprint
Comparing model performances on benchmark datasets is an integral part of measuring and driving progress in artificial intelligence. A model's performance on a benchmark dataset is commonly assessed based on a single or a small set of performance metrics. While this enables quick comparisons, it may also entail the risk of inadequately reflecting m...
Preprint
Skin cancer is among the most common cancer types. Dermoscopic image analysis improves the diagnostic accuracy for detection of malignant melanoma and other pigmented skin lesions when compared to unaided visual inspection. Hence, computer-based methods to support medical experts in the diagnostic procedure are of great interest. Fine-tuning pre-tr...
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(1) Background: Cardiac amyloidosis (CA) is a rare and complex condition with poor prognosis. While novel therapies improve outcomes, many affected individuals remain undiagnosed due to a lack of awareness among clinicians. This study was undertaken to develop an expert-independent machine learning (ML) prediction model for CA relying on routinely...
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Background Cognitive neuroscientists aim to understand behavior often based on the underlying activity of individual neurons. Recently developed miniaturized epifluorescence microscopes allow recording of cellular calcium transients, resembling neuronal activity, of individual neurons even in deep brain areas in freely behaving animals. At the same...
Article
Germline variations in the BRCA‐1 and BRCA‐2 genes are associated with an increased risk of breast cancer. These variants are found in 5% of all breast cancer cases. Prophylactic mastectomy is the most effective risk‐reducing method and shows high rates of patient satisfaction and acceptance. We established a registry of Austrian BRCA‐1 and BRCA‐2...
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Background and Objective: Skin cancer is among the most common cancer types in the white population and consequently computer aided methods for skin lesion classification based on dermoscopic images are of great interest. A promising approach for this uses transfer learning to adapt pre-trained convolutional neural networks (CNNs) for skin lesion d...
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Schizophrenia is characterized by increased behavioral and neurochemical responses to dopamine-releasing drugs. This prompted the hypothesis of psychosis as a state of "endogenous" sensitization of the dopamine system although the exact basis of dopaminergic disturbances and the possible role of prefrontal cortical regulation have remained uncertai...
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Background and Objective: Capturing the context of text is a challenging task in biomedical text summarization. The objective of this research is to show how contextualized embeddings produced by a deep bidirectional language model can be utilized to quantify the informative content of sentences in biomedical text summarization. Methods: We propose...
Article
Background/Introduction Cardiac amyloidosis (CA) is a rare and complex condition with poor prognosis. Novel therapies have been shown to improve outcome, however, most of the affected individuals remain undiagnosed, mainly due to a lack in awareness among clinicians. One approach to overcome this issue is to use automated diagnostic algorithms that...
Article
Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into “violent” versus “non-violent” method. Interestingly, since the proposition of this dichotomous differentiation, no further efforts have been made to question the validity of such a classifi...
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Cross frequency coupling is used to study the cross talk between brain oscillations. In this paper we focus on a special type of frequency coupling between brain and body oscillations, which is reflected by the numerical ratio (r) between two frequencies (m and n; n > m). This approach is motivated by theoretical considerations, indicating that dur...
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Research on machine learning approaches for upper limb prosthesis control has shown impressive progress. However, translating these results from the lab to patient's everyday lives remains a challenge, because advanced control schemes tend to break down under everyday disturbances, such as electrode shifts. Recently, it has been suggested to apply...
Book
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61 Autorinnen und Autoren aus Deutschland, Österreich, der Schweiz, Italien, Frankreich, Kanada, Großbritannien und Australien geben aktuelle Praxistipps und informieren über Ergebnisse und Trends. In einer Bilanz über 25 Jahre Arbeitsgruppe Pädiatrie der Deutschen Gesellschaft für Schlafforschung und Schlafmedizin (DGSM) ist eine umfangreiche List...
Article
Background: Subpectoral implant positioning has been the standard of care in breast reconstruction despite involving disadvantages owing to the detachment of the pectoralis major muscle such as disruption of the muscle function, animation deformities and prolonged postoperative pain. Refined ablative techniques as well as dermal matrices and synthe...
Preprint
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As societies around the world are ageing, the number of Alzheimer's disease (AD) patients is rapidly increasing. To date, no low-cost, non-invasive biomarkers have been established to advance the objectivization of AD diagnosis and progression assessment. Here, we utilize Bayesian neural networks to develop a multivariate predictor for AD severity...
Article
Neuronal signals in the prefrontal cortex have been reported to predict upcoming decisions. Such activity patterns are often coupled to perceptual cues indicating correct choices or values of different options. How does the prefrontal cortex signal future decisions when no cues are present but when decisions are made based on internal valuations of...
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Background: So far, no cost-efficient, widely-used biomarkers have been established to facilitate the objectivization of Alzheimer's disease (AD) diagnosis and monitoring. Research suggests that event-related potentials (ERPs) reflect neurodegenerative processes in AD and might qualify as neurophysiological AD markers. Objectives: First, to examine...
Preprint
Full-text available
Cross frequency coupling is used intensively to study the cross talk between brain oscillations. In this paper we focus on a special type of frequency coupling between brain and body oscillations, which is reflected by the numerical ratio (r) between two frequencies (m and n; n > m). This approach is motivated by theoretical considerations indicati...
Article
Background Previous research suggests significant increases in suicide mortality rates in European countries following the economic crisis of 2008. However, the relationship between national differences in availability and use of mental health services and suicide rates has not been extensively examined yet. Materials and methods Data on mental...
Poster
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OBJECTIVE - The aim of this study was to examine sleep architecture of patients who suffered a stroke using a cohort of healthy individuals as a control group. Methods Subjects. The cohort of stroke patients consisted of patients of the 1 st Department of Neurology of the Faculty of Medicine of the Comenius University in Bratislava and was recorded...
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Bacteraemia is a life-threating condition requiring immediate diagnostic and therapeutic actions. Blood culture (BC) analyses often result in a low true positive result rate, indicating its improper usage. A predictive model might assist clinicians in deciding for whom to conduct or to avoid BC analysis in patients having a relevant bacteraemia ris...
Article
Background: Seltorexant is a potent and selective antagonist of the orexin-2 receptor that is being developed for the treatment of insomnia and major depressive disorder. Aims: The primary objective was to investigate the effect of seltorexant on sleep efficiency after single and multiple dose administration in subjects with insomnia disorder wi...
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Coordinated shifts of neuronal activity in the prefrontal cortex are associated with strategy adaptations in behavioural tasks, when animals switch from following one rule to another. However, network dynamics related to multiple-rule changes are scarcely known. We show how firing rates of individual neurons in the prelimbic and cingulate cortex co...
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The diagnosis of Alzheimer's disease (AD) in routine clinical practice is most commonly based on subjective clinical interpretations. Quantitative electroencephalography (QEEG) measures have been shown to reflect neurodegenerative processes in AD and might qualify as affordable and thereby widely available markers to facilitate the objectivization...
Article
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Background Seasonal changes and climatic factors like ambient temperature, sunlight duration and rainfall can influence suicidal behavior. Methods This study analyses the relationship between seasonal changes and climatic variations and suicide attempts in 2131 young patients in Istanbul, Turkey. ResultsIn our study sample, there was an association...
Article
Event-Related Potentials (ERPs) are commonly used in Neuroscience research, particularly the P3 waveform because it is associated with cognitive brain functions and is easily elicited by auditory or sensory inputs. ERPs are affected by drugs such as lorazepam, which increase the latency and decrease the amplitude of the P3 wave. In this study, audi...
Conference Paper
Myoelectric signals (EMG) provide an intuitive and rapid interface for controlling technical devices, in particular bionic arm prostheses. However, inferring the intended movement from a surface EMG recording is a non-trivial pattern recognition task, especially if the data stems from low-cost sensors. At the same time, overly complex models are pr...
Conference Paper
Full-text available
Event-related potentials (ERPs) have been shown to reflect neurodegenerative processes in Alzheimer’s disease (AD) and might qualify as non-invasive and cost-effective markers to facilitate the objectivization of AD assessment in daily clinical practice. Lately, the combination of multivariate pattern analysis (MVPA) and Gaussian process classifica...