AIMC Topic: Neural Networks, Computer

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A neural network for prediction of risk of nosocomial infection at intensive care units: a didactic preliminary model.

Einstein (Sao Paulo, Brazil)
OBJECTIVE: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infection at intensive care units.

A data driven methodology for social science research with left-behind children as a case study.

PloS one
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...

Automatic eye localization for hospitalized infants and children using convolutional neural networks.

International journal of medical informatics
BACKGROUND: Reliable localization and tracking of the eye region in the pediatric hospital environment is a significant challenge for clinical decision support and patient monitoring applications. Existing work in eye localization achieves high perfo...

Test-time adaptable neural networks for robust medical image segmentation.

Medical image analysis
Convolutional Neural Networks (CNNs) work very well for supervised learning problems when the training dataset is representative of the variations expected to be encountered at test time. In medical image segmentation, this premise is violated when t...

OPUS-Rota3: Improving Protein Side-Chain Modeling by Deep Neural Networks and Ensemble Methods.

Journal of chemical information and modeling
Side-chain modeling is critical for protein structure prediction since the uniqueness of the protein structure is largely determined by its side-chain packing conformation. In this paper, differing from most approaches that rely on rotamer library sa...

A Machine Learning Enabled Wireless Intracranial Brain Deformation Sensing System.

IEEE transactions on bio-medical engineering
A leading cause of traumatic brain injury (TBI) is intracranial brain deformation due to mechanical impact. This deformation is viscoelastic and differs from a traditional rigid transformation. In this paper, we describe a machine learning enabled wi...

Prediction of the outlet flow temperature in a flat plate solar collector using artificial neural network.

Environmental monitoring and assessment
In the current research, the efficiency of a solar flat plate collector (SFPC) was examined experimentally, while the system was modeled with an artificial neural network (ANN) under semi-arid weather conditions of Rafsanjan, Iran. Based on the backp...

Comparison of deep learning with regression analysis in creating predictive models for SARS-CoV-2 outcomes.

BMC medical informatics and decision making
BACKGROUND: Accurately predicting patient outcomes in Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could aid patient management and allocation of healthcare resources. There are a variety of methods which can be used to develop progno...

Supervised machine learning tools: a tutorial for clinicians.

Journal of neural engineering
In an increasingly data-driven world, artificial intelligence is expected to be a key tool for converting big data into tangible benefits and the healthcare domain is no exception to this. Machine learning aims to identify complex patterns in multi-d...

Frequency and phase correction of J-difference edited MR spectra using deep learning.

Magnetic resonance in medicine
PURPOSE: To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data.