Showing results for "andreas holzinger"

The process of doing an academic work, whether a mini-project, diploma thesis, master’s thesis or PhD thesis, requires systematic knowledge and skills in order to answer the following questions: “How do I find a topic?”, “How do I obtain funding money?”, “How do I write a project proposal?”, “How is the organisatoric workflow?“, “How do I search Literature systematically?”, “Why should I read patents?”, “How can I organize my references?”, “Why English as a working language?”, “What is the...

Medical Informatics is defined as an interdisciplinary field studying the effective use of biomedical data, information and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health. To emphasize the broad character it is called Biomedical Informatics. The course LV 444.152 consists of the following 12 lectures: 1. Introduction: Computer Science meets Life Sciences, challenges and future directions; 2. Back to the future: Fundament...

This book provides a broad overview of the topic Bioinformatics with focus on data, information and knowledge. From data acquisition and storage to visualization, ranging through privacy, regulatory and other practical and theoretical topics, the author touches several fundamental aspects of the innovative interface between Medical and Technology domains that is Biomedical Informatics. Each chapter starts by providing a useful inventory of definitions and commonly used acronyms for each to...

Establishment, development and management of a successful research and development group require systematic knowledge and skills and a target-oriented process model. It begins with a vision and requires a clear mission and accordant strategy in order to achieve these goals. The people involved in the team work are of primary importance; everything depends on the interaction of this team. To create this team, to develop, scaffold, advance and lead is a challenge. However, even the best team...

This book constitutes selected papers of the Fourth International Conference on Computer-Human Interaction Research and Applications, CHIRA 2020, held virtually, in November 2020.The 8 full papers presented in this book were carefully reviewed and selected from 44 submissions. The papers selected to be included in this book contribute to the understanding of relevant trends of current research on computer-human interaction, including Interaction design, human factors, entertainment...

Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “bi...

Providing a comprehensive introduction into an overview of the field of pervasive healthcare applications, this volume incorporates a variety of timely topics ranging from medical sensors and hardware infrastructures, to software platforms and applications and addresses issues of user experience and technology acceptance.The recent developments in the area of information and communication technologies have laid the groundwork for new patient-centred healthcare solutions. While the ...

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support.Moreov...

This is an open access book.Statistical machine learning (ML) has triggered a renaissance of artificial intelligence (AI). While the most successful ML models, including Deep Neural Networks (DNN), have developed better predictivity, they have become increasingly complex, at the expense of human interpretability (correlation vs. causality). The field of explainable AI (xAI) has emerged with the goal of creating tools and models that are both predictive and interpretable and underst...

This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022.The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privac...

Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investi...

Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization.Tackling complex challenges needs both disciplinary excellenc...