AIMC Topic: Algorithms

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Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

IEEE transactions on neural networks and learning systems
Early time series classification predicts the class label of a given time series before it is completely observed. In time-critical applications, such as arrhythmia monitoring in ICU, early treatment contributes to the patient's fast recovery, and ea...

Detection method of organic light-emitting diodes based on small sample deep learning.

PloS one
In order to solve the surface detection problems of low accuracy, low precision and inability to automate in the production process of late-model display panels, a little sample-based deep learning organic light-emitting diodes detection model SmartM...

Synchronous Mutual Learning Network and Asynchronous Multi-Scale Embedding Network for miRNA-Disease Association Prediction.

Interdisciplinary sciences, computational life sciences
MicroRNA (miRNA) serves as a pivotal regulator of numerous cellular processes, and the identification of miRNA-disease associations (MDAs) is crucial for comprehending complex diseases. Recently, graph neural networks (GNN) have made significant adva...

Early detection of late-onset neonatal sepsis from noninvasive biosignals using deep learning: A multicenter prospective development and validation study.

International journal of medical informatics
BACKGROUND: Neonatal sepsis is responsible for significant morbidity and mortality worldwide. Its accurate and timely diagnosis is hindered by vague symptoms and the urgent necessity for early antibiotic intervention. The gold standard for diagnosing...

Enhanced Noise-Resilient Pressure Mat System Based on Hyperdimensional Computing.

Sensors (Basel, Switzerland)
Traditional systems for indoor pressure sensing and human activity recognition (HAR) rely on costly, high-resolution mats and computationally intensive neural network-based (NN-based) models that are prone to noise. In contrast, we design a cost-effe...

Deep learning-based algorithms for low-dose CT imaging: A review.

European journal of radiology
The computed tomography (CT) technique is extensively employed as an imaging modality in clinical settings. The radiation dose of CT, however, is significantly high, thereby raising concerns regarding the potential radiation damage it may cause. The ...

The openOCHEM consensus model is the best-performing open-source predictive model in the First EUOS/SLAS joint compound solubility challenge.

SLAS discovery : advancing life sciences R & D
The EUOS/SLAS challenge aimed to facilitate the development of reliable algorithms to predict the aqueous solubility of small molecules using experimental data from 100 K compounds. In total, hundred teams took part in the challenge to predict low, m...

The impacts of active and self-supervised learning on efficient annotation of single-cell expression data.

Nature communications
A crucial step in the analysis of single-cell data is annotating cells to cell types and states. While a myriad of approaches has been proposed, manual labeling of cells to create training datasets remains tedious and time-consuming. In the field of ...

Influence of exposure protocol, voxel size, and artifact removal algorithm on the trueness of segmentation utilizing an artificial-intelligence-based system.

Journal of prosthodontics : official journal of the American College of Prosthodontists
PURPOSE: To evaluate the effects of exposure protocol, voxel sizes, and artifact removal algorithms on the trueness of segmentation in various mandible regions using an artificial intelligence (AI)-based system.