AIMC Topic: Neural Networks, Computer

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Multi-modal infusion pump real-time monitoring technique for improvement in safety of intravenous-administration patients.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Intravenous (IV) medication administration processes have been considered as high-risk steps, because accidents during IV administration can lead to serious adverse effects, which can deteriorate the therapeutic effect or threaten the patient's life....

Lake water-level fluctuation forecasting using machine learning models: a systematic review.

Environmental science and pollution research international
Lake water-level fluctuation is a complex and dynamic process, characterized by high stochasticity and nonlinearity, and difficult to model and forecast. In recent years, applications of machine learning (ML) models have yielded substantial progress ...

Learning hidden patterns from patient multivariate time series data using convolutional neural networks: A case study of healthcare cost prediction.

Journal of biomedical informatics
OBJECTIVE: To develop an effective and scalable individual-level patient cost prediction method by automatically learning hidden temporal patterns from multivariate time series data in patient insurance claims using a convolutional neural network (CN...

Scheduling Sensor Duty Cycling Based on Event Detection Using Bi-Directional Long Short-Term Memory and Reinforcement Learning.

Sensors (Basel, Switzerland)
A smart home provides a facilitated environment for the detection of human activity with appropriate Deep Learning algorithms to manipulate data collected from numerous sensors attached to various smart things in a smart home environment. Human activ...

Diagnosis of left ventricular hypertrophy using convolutional neural network.

BMC medical informatics and decision making
BACKGROUND: Clinically, doctors obtain the left ventricular posterior wall thickness (LVPWT) mainly by observing ultrasonic echocardiographic video stream to capture a single frame of images with diagnostic significance, and then mark two key points ...

A deep learning network-assisted bladder tumour recognition under cystoscopy based on Caffe deep learning framework and EasyDL platform.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Cystoscopy plays an important role in the diagnosis of bladder tumours. As a typical representative of the deep learning algorithm, the convolutional neural network has shown great advantages in the field of image recognition and segmenta...

Virus identification in electron microscopy images by residual mixed attention network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Virus identification in electron microscopy (EM) images is considered as one of the front-line method in pathogen diagnosis and re-emerging infectious agents. However, the existing methods either focused on the detection of ...

Learning patterns of the ageing brain in MRI using deep convolutional networks.

NeuroImage
Both normal ageing and neurodegenerative diseases cause morphological changes to the brain. Age-related brain changes are subtle, nonlinear, and spatially and temporally heterogenous, both within a subject and across a population. Machine learning mo...

Genome-wide association study-based deep learning for survival prediction.

Statistics in medicine
Informative and accurate survival prediction with individualized dynamic risk profiles over time is critical for personalized disease prevention and clinical management. The massive genetic data, such as SNPs from genome-wide association studies (GWA...

Comparing biological and artificial vision systems: Network measures of functional connectivity.

Neuroscience letters
Advances in Deep Convolutional Neural Networks (DCNN) provide new opportunities for computational neuroscience to pose novel questions regarding the function of biological visual systems. Some attempts have been made to utilize advances in machine le...