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Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images.

Medical physics
PURPOSE: It is very important for calculation of clinical indices and diagnosis to detect thyroid nodules from ultrasound images. However, this task is a challenge mainly due to heterogeneous thyroid nodules with distinct components are similar to ba...

A bag-of-paths framework for network data analysis.

Neural networks : the official journal of the International Neural Network Society
This work develops a generic framework, called the bag-of-paths (BoP), for link and network data analysis. The central idea is to assign a probability distribution on the set of all paths in a network. More precisely, a Gibbs-Boltzmann distribution i...

Synchronised firing patterns in a random network of adaptive exponential integrate-and-fire neuron model.

Neural networks : the official journal of the International Neural Network Society
We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections,...

A Hybrid Knowledge-Based and Empirical Scoring Function for Protein-Ligand Interaction: SMoG2016.

Journal of chemical information and modeling
We present the third generation of our scoring function for the prediction of protein-ligand binding free energy. This function is now a hybrid between a knowledge-based potential and an empirical function. We constructed a diversified set of ∼1000 c...

Probability matching in perceptrons: Effects of conditional dependence and linear nonseparability.

PloS one
Probability matching occurs when the behavior of an agent matches the likelihood of occurrence of events in the agent's environment. For instance, when artificial neural networks match probability, the activity in their output unit equals the past pr...

Identifying the missing proteins in human proteome by biological language model.

BMC systems biology
BACKGROUND: With the rapid development of high-throughput sequencing technology, the proteomics research becomes a trendy field in the post genomics era. It is necessary to identify all the native-encoding protein sequences for further function and p...

MUMAL2: Improving sensitivity in shotgun proteomics using cost sensitive artificial neural networks and a threshold selector algorithm.

BMC bioinformatics
BACKGROUND: This work presents a machine learning strategy to increase sensitivity in tandem mass spectrometry (MS/MS) data analysis for peptide/protein identification. MS/MS yields thousands of spectra in a single run which are then interpreted by s...

Lung Cancer Classification Employing Proposed Real Coded Genetic Algorithm Based Radial Basis Function Neural Network Classifier.

Computational and mathematical methods in medicine
A proposed real coded genetic algorithm based radial basis function neural network classifier is employed to perform effective classification of healthy and cancer affected lung images. Real Coded Genetic Algorithm (RCGA) is proposed to overcome the ...

PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures.

Forensic science international. Genetics
The deconvolution of DNA mixtures remains one of the most critical challenges in the field of forensic DNA analysis. In addition, of all the data features required to perform such deconvolution, the number of contributors in the sample is widely cons...

Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

International journal of computer assisted radiology and surgery
PURPOSE: Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propo...