AIMC Topic: Algorithms

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Survival Analysis with High-Dimensional Omics Data Using a Threshold Gradient Descent Regularization-Based Neural Network Approach.

Genes
Analysis of data with a censored survival response and high-dimensional omics measurements is now common. Most of the existing analyses are based on specific (semi)parametric models, in particular the Cox model. Such analyses may be limited by not ha...

A Comprehensive Assessment of Cultivation Environment of Top Innovative High-Level Talents Based on Deep Learning Algorithm.

Journal of environmental and public health
The quality of talent has increased across all fields due to the constant growth of different industries and the growing job saturation. Real-time job information on recruitment platforms can, therefore, accurately reflect the demand for talent from ...

Impact of Financial Development on Income Gap Based on Improved Gaussian Kernel Function and BGP Anomaly Detection.

Computational intelligence and neuroscience
Nuclear methods, such as the study of the main components of nuclear and the support of vector machines, have gradually evolved into a type of pillar methods for pattern recognition and economic statistics. Therefore, how to choose the inner product ...

Application of Combination Forecasting Model in Aircraft Failure Rate Forecasting.

Computational intelligence and neuroscience
Effective prediction of aircraft failure rate has important guiding significance for formulating reasonable maintenance plans, carrying out reliable maintenance activities, improving health management levels, and ensuring the safety of aircraft fligh...

A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents.

PloS one
Spontaneous synaptic activity is a hallmark of biological neural networks. A thorough description of these synaptic signals is essential for understanding neurotransmitter release and the generation of a postsynaptic response. However, the complexity...

Deep learning image reconstruction to improve accuracy of iodine quantification and image quality in dual-energy CT of the abdomen: a phantom and clinical study.

European radiology
OBJECTIVES: To investigate the effect of deep learning image reconstruction (DLIR) on the accuracy of iodine quantification and image quality of dual-energy CT (DECT) compared to that of other reconstruction algorithms in a phantom experiment and an ...

Switching pinning control for memristive neural networks system with Markovian switching topologies.

Neural networks : the official journal of the International Neural Network Society
This work concentrates on the issue of leader-following bipartite synchronization of multiple memristive neural networks with Markovian jump topology. In contrast to conventional coupled neural network systems, the coupled neural network model under ...

Gaze-assisted automatic captioning of fetal ultrasound videos using three-way multi-modal deep neural networks.

Medical image analysis
In this work, we present a novel gaze-assisted natural language processing (NLP)-based video captioning model to describe routine second-trimester fetal ultrasound scan videos in a vocabulary of spoken sonography. The primary novelty of our multi-mod...

Mitigating urinary incontinence condition using machine learning.

BMC medical informatics and decision making
BACKGROUND: Urinary incontinence (UI) is the inability to completely control the process of releasing urine. UI presents a social, medical, and mental issue with financial consequences.

Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials.

Journal of chemical information and modeling
Computational programs accelerate the chemical discovery processes but often need proper three-dimensional molecular information as part of the input. Getting optimal molecular structures is challenging because it requires enumerating and optimizing ...