Entries by Andreas Holzinger

Call for Papers: Open Data for Discovery Science (due to July, 31, 2017)

The Journal BMC Medical Informatics and Decision Making (SCI IF (2015): 2,042) invites to submit to a new thematic series on open data for discovery science https://bmcmedinformdecismak.biomedcentral.com/articles/collections/odds Note: Excellent submissions to the IFIP Cross Domain Conference on Machine Learning and Knowledge Discovery (CD-MAKE), (Submission due to May, 15, 2017) relevant to the topics described below, […]

Federated Collaborative Machine Learning

The Google Research Group [1] is always doing awesome stuff, the most recent one is on Federated Learning [2], which enables e.g. smart phones (of course any computational device, and maybe later all internet-of-things, intelligent sensors in either smart hospitals or in smart factories etc.) to collaboratively learn a shared representation model, whilst keeping all […]

Integrated interactomes and pathways in precision medicine by Igor Jurisica, Toronto

Machine learning is the fastest growing field in computer science, and Health Informatics is amongst the greatest application challenges, providing benefits in improved medical diagnoses, disease analyses, and pharmaceutical development – towards future precision medicine. Talk announcement: Friday, 12th May, 2017, 10:00, Seminaraum 137, Parterre, Inffeldgasse 16c Integrated interactomes and pathways in precision medicine by […]

What is machine learning?

Many services of our every day life rely meanwhile on machine learning – a field of science and a powerful technology that allows machines to learn from data; a very nice info graphic by the Royal Society – interactive with a quiz – can be found here: Royal Society Infographic “What is machine learning?” This […]

Machine Learning Guide

An excellent podcast which I can fully recommend to my students is the Machine Learning Guide by Tyler RENELLE (Tensor Flow). This series aims to teach the high level fundamentals of machine learning with a focus on algorithms and some underlying mathematics, which is really great. http://ocdevel.com/podcasts/machine-learning      

Cross Domain Conference for Machine Learning & Knowledge Extraction

cd-make.net Call for Papers – due to May, 15, 2017 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=61244&copyownerid=17803 Call for Papers due to May, 15, 2017 International IFIP Cross Domain Conference for Machine Learning & Knowledge Extraction CD-MAKE in Reggio di Calabria (Italy) August 29 – September 1, 2017 https://cd-make.net CD stands for Cross-Domain and means the integration and appraisal of different […]

Stan: A probabilistic programming language

A long time ago submitted paper from the Stan developers http://mc-stan.org/ has finally been appeared at the Journal of statistical software: https://www.jstatsoft.org Carpenter, B., Gelman, A., Hoffman, M., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M. A., Guo, J., Li, P. & Riddell, A. 2017. Stan: A probabilistic programming language. Journal of Statistical Software, 76, […]

Call for Papers – Privacy Aware Machine Learning PAML due to April, 1, 2017

Privacy Aware Machine Learning (PAML) for Health Data Science Special Session on September, 1, 2017, organized by Andreas HOLZINGER, Peter KIESEBERG, Edgar WEIPPL and A Min TJOA in the context of the 12th International Conference on Availability, Reliability and Security (ARES and CD-ARES), Reggio di Calabria, Italy, August 29 – September, 2, 2017 Session Homepage […]

3,2 Trillion USD on health per year

The U.S. spends more on health care than any other country Dieleman et al. (2016) just (Dec, 27, 2016) published a paper [1] which discusses data from the National Health Expenditure Accounts to estimate US spending on personal health care and public health, according to condition, age and sex group, and type of care. This […]