AIMC Topic: Algorithms

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Automatic quantification of the LV function and mass: A deep learning approach for cardiovascular MRI.

Computer methods and programs in biomedicine
OBJECTIVE: This paper proposes a novel approach for automatic left ventricle (LV) quantification using convolutional neural networks (CNN).

Synchronization in uncertain fractional-order memristive complex-valued neural networks with multiple time delays.

Neural networks : the official journal of the International Neural Network Society
This paper considers the global asymptotical synchronization of fractional-order memristive complex-valued neural networks (FOMCVNN), with both parameter uncertainties and multiple time delays. Sufficient conditions of uncertain FOMCVNN, with multipl...

Applying Machine Learning Algorithms to Segment High-Cost Patient Populations.

Journal of general internal medicine
BACKGROUND: Efforts to improve the value of care for high-cost patients may benefit from care management strategies targeted at clinically distinct subgroups of patients.

P_VggNet: A convolutional neural network (CNN) with pixel-based attention map.

PloS one
Attention maps have been fused in the VggNet structure (EAC-Net) [1] and have shown significant improvement compared to that of the VggNet structure. However, in [1], E-Net was designed based on the facial action unit (AU) center and for facial AU de...

What is a cognitive map? Unravelling its mystery using robots.

Cognitive processing
Despite years of research into cognitive mapping, the process remains controversial and little understood. A computational theory of cognitive mapping is needed, but developing it is difficult due to the lack of a clear interpretation of the empirica...

Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning.

Radiology
Purpose To develop and evaluate a fully automated algorithm for segmenting the abdomen from CT to quantify body composition. Materials and Methods For this retrospective study, a convolutional neural network based on the U-Net architecture was traine...

SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.

PLoS computational biology
LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational ...

A novel approach to predicting human ingress motion using an artificial neural network.

Journal of biomechanics
Due to the increased availability of digital human models, the need for knowing human movement is important in product design process. If the human motion is derived rapidly as design parameters change, a developer could determine the optimal paramet...

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier.

International journal of medical informatics
PURPOSE: Sepsis is a life-threatening condition with high mortality rates and expensive treatment costs. To improve short- and long-term outcomes, it is critical to detect at-risk sepsis patients at an early stage.