Zero-shot learning (ZSL) aims to recognize unseen objects (test classes) given some other seen objects (training classes) by sharing information of attributes between different objects. Attributes are artificially annotated for objects and treated eq...
With qPCR reaching thousands of reactions per run, assay validation needs automation. We applied support vector machine to qPCR analysis and we could identify reactions with 100% accuracy, dispensing them from further validation. We achieved a greatl...
In this paper we define the concept of the Machine Learning Morphism (MLM) as a fundamental building block to express operations performed in machine learning such as data preprocessing, feature extraction, and model training. Inspired by statistical...
Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
Nov 13, 2019
To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neural network (dCNN) was trained to combine single- and multi-delay arterial spin labeling (ASL) and structural images to predict gold-standard O-water ...
BACKGROUND: Machine learning can effectively nominate novel genes for various research purposes in the laboratory. On a genome-wide scale, we implemented multiple databases and algorithms to predict and prioritize the human aging genes (PPHAGE).
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a larg...
With the rapid development of the internet, social media has become an essential tool for getting information, and attracted a large number of people join the social media platforms because of its low cost, accessibility and amazing content. It great...
We show that Cohen's Kappa and Matthews Correlation Coefficient (MCC), both extended and contrasted measures of performance in multi-class classification, are correlated in most situations, albeit can differ in others. Indeed, although in the symmetr...
Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics has emerged as a valuable tool for biological discovery, capable of assaying thousands of diverse chemical entities in a single biospecimen. Processing of nontargeted LC-MS spectral d...
Computational intelligence and neuroscience
Sep 16, 2019
The integration of machine learning techniques and metaheuristic algorithms is an area of interest due to the great potential for applications. In particular, using these hybrid techniques to solve combinatorial optimization problems (COPs) to improv...