Efficiency, memory consumption, and robustness are common problems with many popular methods for data analysis. As a solution, we present Random Bits Forest (RBF), a classification and regression algorithm that integrates neural networks (for depth),...
Theory in biosciences = Theorie in den Biowissenschaften
Jul 21, 2016
In this paper, we show how the development of plastic behaviours, i.e., behaviour displaying a modular organisation characterised by behavioural subunits that are alternated in a context-dependent manner, can enable evolving robots to solve their ada...
BMC medical informatics and decision making
Jul 21, 2016
BACKGROUND: People want to live independently, but too often disabilities or advanced age robs them of the ability to do the necessary activities of daily living (ADLs). Finding relationships between electromyograms measured in the arm and movements ...
BMC medical informatics and decision making
Jul 21, 2016
BACKGROUND: Cancer is a disease characterized as an uncontrolled growth of abnormal cells that invades neighboring tissues and destroys them. Lung cancer is the primary cause of cancer-related deaths in the world, and it diagnosis is a complex task f...
BMC medical informatics and decision making
Jul 21, 2016
BACKGROUND: Longitudinal data sources, such as electronic health records (EHRs), are very valuable for monitoring adverse drug events (ADEs). However, ADEs are heavily under-reported in EHRs. Using machine learning algorithms to automatically detect ...
BMC medical informatics and decision making
Jul 21, 2016
BACKGROUND: Epileptic seizure is a serious health problem in the world and there is a huge population suffering from it every year. If an algorithm could automatically detect seizures and deliver the patient therapy or notify the hospital, that would...
BMC medical informatics and decision making
Jul 21, 2016
BACKGROUND: Learning deep representations of clinical events based on their distributions in electronic health records has been shown to allow for subsequent training of higher-performing predictive models compared to the use of shallow, count-based ...
In this paper we apply machine learning methods for predicting protein interactions in fungal secretion pathways. We assume an inter-species transfer setting, where training data is obtained from a single species and the objective is to predict prote...
Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for VF-detection are customarily...
Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multipl...
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