Marta’s, Sebastian’s and Theo’s abstracts have been accepted at the ECDA 2019 and they will give talks on A novel privacy-preserving software framework for federated machine learning in clinical settings and A comparative study on peptide encodings for biomedical classification and Illuminating interactions in microbial lake ecology using General Learning Chain Ensembles respectively.
Our new article has been accepted in BMC Bioinformatics: Sperlea T, Füser S, Boenigk J, Heider D: SEDE-GPS: socio-economic data enrichment based on GPS information. BMC Bioinformatics 2018, 19(Suppl 15):440. (Link) Abstract Background Microbes are essentail components of all ecosystems because they drive many biochemical processes and act as primary producers. In freshwater ecosystems, the…
Our new article has been accepted in Bioinformatics: Schwarz J and Heider D: GUESS: Projecting Machine Learning Scores to Well-Calibrated Probability Estimates for Clinical Decision Making. Bioinformatics 2018, in press. Abstract Motivation: Clinical decision-support-systems (CDSS) have been applied in numerous fields, ranging from cancer survival towards drug resistance prediction. Nevertheless, CDSS typically have a caveat:…
Angelo Facchiano and Dominik Heider will host a special issue on Artificial Intelligence Bioinformatics: Development and Application of Tools for Omics and Inter-Omics Studies Omics sciences revolutionized research in areas such as biology, biotechnology, medicine, and agri-food sciences. With the novelty of high-throughput techniques, researchers may encounter difficulties to manage and interpret the huge amount…
Dominik is member of the program commitee of the ECDA 2019 in Bayreuth. ECDA solicits contributions to theoretical as well as application-oriented research on topics in the realm of data science, with a specific focus on data analytics. With its motto „Multidisciplinary Facets of Data Science“, ECDA 2019 specifically emphasizes the important interplay of disciplines…
Our new article has been accepted in Machine Learning and Knowledge Extraction: Armano G, Giuliani A, Neumann U, Rothe N, Heider D: Phi-Delta-Diagrams: Software Implementation of a Visual Tool for Assessing Classifier and Feature Performance. Mach. Learn. Knowl. Extr. 2018, 1(1):7 (Link) Abstract In this article, a two-tiered 2D tool is described, called phi-delta diagrams, and…
Ulla’s and Johanna’s abstracts have been accepted at the ECDA 2018 and they will give talks on Ensemble Feature Selection for Regression Problems and On the projection of machine learning scores to well-calibrated probability estimates respectively.
Our new article has been accepted in Archives of Medical Science: Baars T, Sowa J-P, Neumann U, Hendricks S, Jinawy M, Kälsch J, Gerken G, Rassaf T, Heider D, Canbay A: Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction. Archives of Medical Science 2018, in press. Abstract…
Our new article has been accepted in Systems Medicine: Riemenschneider R, Wienbeck J, Scherag A, Heider D: Data Science for MDx Applications: From Academia to Clinic to Industry. Systems Medicine 2018, in press. Abstract The development of computational approaches for predictive modeling of diseases, e.g., in cancer diagnostics or prognostics, or drug resistance predictions in…
Dominik gave a talk on „Machine learning models for molecular diagnostics“ at the University of Bielefeld at the Mini-Workshop on Storage of and Search in Viral Quasispecies 2018.
