MLMA 2016 - Special session on Machine learning for medical applications

Machine learning has been an active research area in the last decades finding success in many different applications, among them in medical problems. Machine learning is capable of automating manual processes carried out by practitioners, which are usually time-consuming and subjective. Therefore, the use of machine learning can save time for practitioners and provide unbiased, repeatable results. Additionally, the large dimensionality of data in medicine together with the common reduced sample size of pathological cases makes indispensable the use of advanced machine learning techniques for clinical interpretation and analysis.
This special session is concerned with using different machine learning techniques or approaches in medical applications. Furthermore, it also aims to offer a meeting opportunity for academics and clinical researchers to present their cutting-edge methods to deal with medical problems and to discuss the new challenges that need to be faced.
We invite papers on machine learning approaches applied to medical problems. In particular, topics of interest include, but are not limited to:
Artificial intelligence in medicine
Clinical interpretation and analysis
Computer-aided detection and diagnosis
Physiological signal analysis
Medical image analysis
Content-based image retrieval
Feature selection and extraction in medicine
Pattern recognition in medicine
Big data in healthcare
Learning in uncertainty labeled data
Bioinformatics and microarray analysis