AIMC Topic: Computer Simulation

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Can supervised deep learning architecture outperform autoencoders in building propensity score models for matching?

BMC medical research methodology
PURPOSE: Propensity score matching is vital in epidemiological studies using observational data, yet its estimates relies on correct model-specification. This study assesses supervised deep learning models and unsupervised autoencoders for propensity...

A machine learning-based predictive model for the in-hospital mortality of critically ill patients with atrial fibrillation.

International journal of medical informatics
BACKGROUND: Atrial fibrillation (AF) is common among intensive care unit (ICU) patients and significantly raises the in-hospital mortality rate. Existing scoring systems or models have limited predictive capabilities for AF patients in ICU. Our study...

Isotopological remeshing and statistical shape analysis: Enhancing premolar tooth wear classification and simulation with machine learning.

Journal of dentistry
OBJECTIVE: The aim of this study was to evaluate the accuracy of a combined approach based on an isotopological remeshing and statistical shape analysis (SSA) to capture key anatomical features of altered and intact premolars. Additionally, the study...

m5c-iDeep: 5-Methylcytosine sites identification through deep learning.

Methods (San Diego, Calif.)
5-Methylcytosine (m5c) is a modified cytosine base which is formed as the result of addition of methyl group added at position 5 of carbon. This modification is one of the most common PTM that used to occur in almost all types of RNA. The conventiona...

A Machine Learning Algorithm to Predict the Starting Dose of Daptomycin.

Clinical pharmacokinetics
BACKGROUND AND OBJECTIVE: The dosage of daptomycin is usually based on body weight. However, it has been shown that this approach yields too high an exposure in obese patients. Pharmacokinetic and pharmacodynamic indexes (PK/PD) have been proposed fo...

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.

Journal of computational neuroscience
The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form ...

Multitask learning of a biophysically-detailed neuron model.

PLoS computational biology
The human brain operates at multiple levels, from molecules to circuits, and understanding these complex processes requires integrated research efforts. Simulating biophysically-detailed neuron models is a computationally expensive but effective meth...

Improved fixed-time stability analysis and applications to synchronization of discontinuous complex-valued fuzzy cellular neural networks.

Neural networks : the official journal of the International Neural Network Society
This article mainly centers on proposing new fixed-time (FXT) stability lemmas of discontinuous systems, in which novel optimization approaches are utilized and more relaxed conditions are required. The conventional discussions about Vt>1 and 0

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.

Journal of magnetic resonance imaging : JMRI
This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as multiparametric MRI for capturing the complex nature o...

Detecting differentially expressed genes from RNA-seq data using fuzzy clustering.

The international journal of biostatistics
A two-group comparison test is generally performed on RNA sequencing data to detect differentially expressed genes (DEGs). However, the accuracy of this method is low due to the small sample size. To address this, we propose a method using fuzzy clus...