AIMC Topic: Neural Networks, Computer

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A water quality prediction method based on the multi-time scale bidirectional long short-term memory network.

Environmental science and pollution research international
As an important factor affecting the mangrove wetland ecosystem, water quality has become the focus of attention in recent years. Therefore, many studies have focused on the prediction of water quality to help establish a regulatory framework for the...

A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods.

Medical & biological engineering & computing
Sperm morphology, as an indicator of fertility, is a critical tool in semen analysis. In this study, a smartphone-based hybrid system that fully automates the sperm morphological analysis is introduced with the aim of eliminating unwanted human facto...

Augmented patient-specific functional medical imaging by implicit manifold learning.

International journal for numerical methods in biomedical engineering
This paper uses machine learning to enrich magnetic resonance angiography and magnetic resonance imaging acquisitions. A convolutional neural network is built and trained over a synthetic database linking geometrical parameters and mechanical charact...

A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets.

Sensors (Basel, Switzerland)
Due to the repercussion of falls on both the health and self-sufficiency of older people and on the financial sustainability of healthcare systems, the study of wearable fall detection systems (FDSs) has gained much attention during the last years. T...

A Novel System for Functional Determination of Variants of Uncertain Significance using Deep Convolutional Neural Networks.

Scientific reports
Many drugs are developed for commonly occurring, well studied cancer drivers such as vemurafenib for BRAF V600E and erlotinib for EGFR exon 19 mutations. However, most tumors also harbor mutations which have an uncertain role in disease formation, co...

Detection of strict left bundle branch block by neural network and a method to test detection consistency.

Physiological measurement
OBJECTIVE: To develop an automatic algorithm to detect strict left bundle branch block (LBBB) on electrocardiograms (ECG) and propose a procedure to test the consistency of neural network detections.

Applying Machine Learning in Liver Disease and Transplantation: A Comprehensive Review.

Hepatology (Baltimore, Md.)
Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently and more effectively than conventional methods through detection of hidden patterns within large data sets. With this in mind, there are several areas wi...

Artificial intelligence and convolution neural networks assessing mammographic images: a narrative literature review.

Journal of medical radiation sciences
Studies have shown that the use of artificial intelligence can reduce errors in medical image assessment. The diagnosis of breast cancer is an essential task; however, diagnosis can include 'detection' and 'interpretation' errors. Studies to reduce t...

Semantic segmentation of the multiform proximal femur and femoral head bones with the deep convolutional neural networks in low quality MRI sections acquired in different MRI protocols.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical image segmentation is one of the most crucial issues in medical image processing and analysis. In general, segmentation of the various structures in medical images is performed for the further image analyzes such as quantification, assessment...