Entries by Andreas Holzinger

A proof of the importance of the human-in-the-loop

Again machine learning made it to the title page of Science: A nice further proof for the importance of the human-in-the-loop by a paper of Lake, B. M., Salakhutdinov, R. & Tenenbaum, J. B. 2015. Human-level concept learning through probabilistic program induction. Science, 350, (6266), 1332-1338. Whilst humans can learn new concepts often from a […]

Workshop “Machine Learning for Health Informatics” November, 30, 2015

Workshop Machine Learning for Health Informatics Machine learning is a large and rapidly developing subfield of computer science that evolved from artificial intelligence (AI) and is tightly connected with data mining and knowledge discovery. The ultimate goal of machine learning is to design and develop algorithms which can learn from data. Consequently, machine learning systems […]

December, 3, 2015 Seminar Talk on human protein interaction networks

Title: Coordination of post-translational modifications in human protein interaction network Lecturer: Ulrich Stelzl, Network Pharmacology, Insitute of Pharmaceutical Sciences, Karl-Franzens University Graz Abstract: Comprehensive protein interaction networks are prerequisite for a better understanding of complex genotype to phenotype relationships. Post – translational modifications (PTMs) regulate protein activity, stability and protein interaction (PPI) profiles critical for […]

July, 7, 2015 Seminar Metabolomics data types

The potential of metabolomics and its various data types Lecturer: Natalie BORDAG,  CBmed – Center for Biomarker Research in Medicine Graz Abstract: Metabolomics is one of the youngest -omics technologies primarily concerned with the identification and quantification of small molecules (<1500 Da). The specific advantage of metabolomics in biomarker research lies in the concept, that […]

July, 7, 2015 Seminar Feature Based Search

Visual-Interactive Search and Exploration in Complex Data Repositories – Feature-Based Search, Applications and Research Challenges Lecturer: Tobias SCHRECK, University of Konstanz and Graz University of Technology <link> Abstract: Advances in data acquisition and storage technology are leading to the creation of large, complex data sets in many different domains including science, engineering or social media. […]

Machine Learning in Nature again

Lecun, Y., Bengio, Y. & Hinton, G. 2015. Deep learning. Nature, 521, (7553), 436-444. Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains […]

June, 23, 2015 Seminar Talk Machine Learning

Title: Towards Knowledge Discovery with the human in the machine learning loop: An Ontology-Guided Meta-Classifying Approach for the Biomedical Domain Lecturer: Dominic GIRADI, RISC-Software Linz, Austria <expertise> Abstract: The process of knowledge discovery in clinical research is significantly different from other business domains, for example market research. While in the general definitions of knowledge discovery […]

May,19, 2015 Seminar Talks Machine Learning

Title: Towards Personalization of Diabetes Therapy Using Computerized Decision Support and Machine Learning Lecturer: Klaus DONSA <expertise> and Stephan SPAT <expertise> Abstract: Diabetes mellitus (DM) is a growing global disease which highly affects the individual patient and represents a global health burden with financial impact on national health care systems. The therapeutic options include lifestyle […]