AIMC Topic:
Computer Simulation
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AI-based pathology predicts origins for cancers of unknown primary.
Nature
May 5, 2021
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primar...
Explaining face representation in the primate brain using different computational models.
Current biology : CB
May 4, 2021
Understanding how the brain represents the identity of complex objects is a central challenge of visual neuroscience. The principles governing object processing have been extensively studied in the macaque face patch system, a sub-network of inferote...
Glycemic and lipid variability for predicting complications and mortality in diabetes mellitus using machine learning.
BMC endocrine disorders
May 4, 2021
INTRODUCTION: Recent studies have reported that HbA1c and lipid variability is useful for risk stratification in diabetes mellitus. The present study evaluated the predictive value of the baseline, subsequent mean of at least three measurements and v...
Efficient Automated Disease Diagnosis Using Machine Learning Models.
Journal of healthcare engineering
May 4, 2021
Recently, many researchers have designed various automated diagnosis models using various supervised learning models. An early diagnosis of disease may control the death rate due to these diseases. In this paper, an efficient automated disease diagno...
Feature importance of machine learning prediction models shows structurally active part and important physicochemical features in drug design.
Drug metabolism and pharmacokinetics
May 3, 2021
The objective of this study was to obtain the indicators of physicochemical parameters and structurally active sites to design new chemical entities with desirable pharmacokinetic profiles by investigating the process by which machine learning predic...
Pseudocell Tracer-A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombination.
PLoS computational biology
May 3, 2021
Single cell RNA sequencing (scRNAseq) can be used to infer a temporal ordering of cellular states. Current methods for the inference of cellular trajectories rely on unbiased dimensionality reduction techniques. However, such biologically agnostic or...
Computer Simulation
Animals
Single-Cell Analysis
Neural Networks, Computer
Interleukin-4
Immunoglobulin G
Signal Transduction
Mice, Inbred C57BL
Gene Expression
B-Lymphocytes
RNA-Seq
Mice
Computational Biology
Immunoglobulin Class Switching
NF-kappa B p50 Subunit
STAT6 Transcription Factor
Receptors, Cytokine
Recombination, Genetic
Supervised Machine Learning
Basic-Leucine Zipper Transcription Factors
Databases, Nucleic Acid
Models, Immunological
Artificial Evolution Network: A Computational Perspective on the Expansibility of the Nervous System.
IEEE transactions on neural networks and learning systems
May 3, 2021
Neurobiologists recently found the brain can use sudden emerged channels to process information. Based on this finding, we put forward a question whether we can build a computation model that is able to integrate a sudden emerged new type of perceptu...
Qualitative Analysis and Bifurcation in a Neuron System With Memristor Characteristics and Time Delay.
IEEE transactions on neural networks and learning systems
May 3, 2021
This article focuses on the hybrid effects of memristor characteristics, time delay, and biochemical parameters on neural networks. First, we propose a novel neuron system with memristor and time delays in which the memristor is characterized by a sm...
Multistability and associative memory of neural networks with Morita-like activation functions.
Neural networks : the official journal of the International Neural Network Society
Apr 30, 2021
This paper presents the multistability analysis and associative memory of neural networks (NNs) with Morita-like activation functions. In order to seek larger memory capacity, this paper proposes Morita-like activation functions. In a weakened condit...
Towards a mathematical framework to inform neural network modelling via polynomial regression.
Neural networks : the official journal of the International Neural Network Society
Apr 30, 2021
Even when neural networks are widely used in a large number of applications, they are still considered as black boxes and present some difficulties for dimensioning or evaluating their prediction error. This has led to an increasing interest in the o...
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