AIMC Topic: Algorithms

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ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm.

Journal of proteome research
The major histocompatibility complex (MHC) is a term for all gene groups of a major histocompatibility antigen. It binds to peptide chains derived from pathogens and displays pathogens on the cell surface to facilitate T-cell recognition and perform ...

Noninvasive prediction of Blood Lactate through a machine learning-based approach.

Scientific reports
We hypothesized that blood lactate concentration([Lac]) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [L...

CirGO: an alternative circular way of visualising gene ontology terms.

BMC bioinformatics
BACKGROUND: Prioritisation of gene ontology terms from differential gene expression analyses in a two-dimensional format remains a challenge with exponentially growing data volumes. Typically, gene ontology terms are represented as tree-maps that enc...

Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images.

Journal of healthcare engineering
This study aimed to develop a machine learning-based algorithm for glaucoma diagnosis in patients with open-angle glaucoma, based on three-dimensional optical coherence tomography (OCT) data and color fundus images. In this study, 208 glaucomatous an...

Phonocardiogram classification using deep neural networks and weighted probability comparisons.

Journal of medical engineering & technology
Cardiac auscultation is one of the most conventional approaches for the initial assessment of heart disease, however the technique is highly user-dependent and with low repeatability. Several computational approaches based on the analysis of the phon...

Time-dependent AI-Modeling of the anticancer efficacy of synthesized gallic acid analogues.

Computational biology and chemistry
BACKGROUND/AIM: Main objective of this study is mapping of the anticancer efficacy of synthesized gallic acid analogues using modeling and artificial intelligence (AI) over a large range of concentrations and exposure times to explore the underline m...

Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness.

Computers in biology and medicine
BACKGROUND: The continuation of life-sustaining therapy in critical care patients with anoxic-ischemic disorders of consciousness (AI-DOC) depends on prognostic tests such as serum neuron-specific enolase (NSE) concentration levels.

A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs.

Journal of computational neuroscience
Homogeneously structured, fluctuation-driven networks of spiking neurons can exhibit a wide variety of dynamical behaviors, ranging from homogeneity to synchrony. We extend our partitioned-ensemble average (PEA) formalism proposed in Zhang et al. (Jo...

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.

International journal of computer assisted radiology and surgery
PURPOSE: Cancers are almost always diagnosed by morphologic features in tissue sections. In this context, machine learning tools provide new opportunities to describe tumor immune cell interactions within the tumor microenvironment and thus provide p...

Contact Modelling and Tactile Data Processing for Robot Skins.

Sensors (Basel, Switzerland)
Tactile sensing is a key enabling technology to develop complex behaviours for robots interacting with humans or the environment. This paper discusses computational aspects playing a significant role when extracting information about contact events. ...