Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a...
Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility, they are characterized by their computationally relevant physical properties, such as their state-d...
Chemical communications (Cambridge, England)
Jan 10, 2019
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...
Laser speckle contrast imaging (LSCI) enables video rate imaging of blood flow. However, its relation to tissue blood perfusion is nonlinear and depends strongly on exposure time. By contrast, the perfusion estimate from the slower laser Doppler flow...
The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a cont...
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2018
A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important...
PURPOSE: The random walk (RW) technique serves as a powerful tool for PET tumor delineation, which typically involves significant noise and/or blurring. One challenging step is hard decision-making in pixel labeling. Fuzzy logic techniques have achie...
IEEE transactions on pattern analysis and machine intelligence
Aug 1, 2015
Tree-like structures are fundamental in nature, and it is often useful to reconstruct the topology of a tree - what connects to what - from a two-dimensional image of it. However, the projected branches often cross in the image: the tree projects to ...
IEEE transactions on neural networks and learning systems
Mar 1, 2015
The stochastic optimal control of nonlinear networked control systems (NNCSs) using neuro-dynamic programming (NDP) over a finite time horizon is a challenging problem due to terminal constraints, system uncertainties, and unknown network imperfectio...
IEEE transactions on neural networks and learning systems
Feb 1, 2015
Learning algorithms play an important role in the practical application of neural networks based on principal component analysis, often determining the success, or otherwise, of these applications. These algorithms cannot be divergent, but it is very...