Accurate monitoring of sedentary behaviour and physical activity is key to investigate their exact role in healthy ageing. To date, accelerometers using cut-off point models are most preferred for this, however, machine learning seems a highly promis...
Sequence classification is crucial in predicting the function of newly discovered sequences. In recent years, the prediction of the incremental large-scale and diversity of sequences has heavily relied on the involvement of machine-learning algorithm...
Journal of the American College of Radiology : JACR
Nov 17, 2017
Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside ...
Tracing the use of computers in the radiology department from administrative functions through image acquisition, storage, and reporting, to early attempts at improved diagnosis, we begin to imagine possible new frontiers for their use in exam interp...
Neural networks : the official journal of the International Neural Network Society
Nov 15, 2017
In this paper, we study global uniform asymptotic fixed deviation stability and stability for a wide class of memristive neural networks with time-varying delays. Firstly, a new mathematical expression of the generic memductance (memristance) is prop...
Neural networks : the official journal of the International Neural Network Society
Nov 15, 2017
Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the develo...
This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-po...
This paper presents novel QSAR models for the prediction of antitrypanosomal activity among thiazolidines and related heterocycles. The performance of four machine learning algorithms: Random Forest regression, Stochastic gradient boosting, Multivari...
We develop two complementary pipelines, "Zhang-Server" and "QUARK", based on I-TASSER and QUARK pipelines for template-based modeling (TBM) and free modeling (FM), and test them in the CASP12 experiment. The combination of I-TASSER and QUARK successf...
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