AIMC Topic: Algorithms

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Research into the Applications of a Multi-Scale Feature Fusion Model in the Recognition of Abnormal Human Behavior.

Sensors (Basel, Switzerland)
Due to the increasing severity of aging populations in modern society, the accurate and timely identification of, and responses to, sudden abnormal behaviors of the elderly have become an urgent and important issue. In the current research on compute...

Improving the quality of Persian clinical text with a novel spelling correction system.

BMC medical informatics and decision making
BACKGROUND: The accuracy of spelling in Electronic Health Records (EHRs) is a critical factor for efficient clinical care, research, and ensuring patient safety. The Persian language, with its abundant vocabulary and complex characteristics, poses un...

Prediction models for retinopathy of prematurity occurrence based on artificial neural network.

BMC ophthalmology
INTRODUCTION: Early prediction and timely treatment are essential for minimizing the risk of visual loss or blindness of retinopathy of prematurity, emphasizing the importance of ROP screening in clinical routine.

Design of a bipedal robot for water running based on a six-linkage mechanism inspired by basilisk lizards.

Bioinspiration & biomimetics
Legged robots have received widespread attention in academia and engineering owing to their excellent terrain adaptability. However, most legged robots can only adapt to high-hardness environments instead of flexible environments. Expanding the motio...

Machine learning of brain-specific biomarkers from EEG.

EBioMedicine
BACKGROUND: Electroencephalography (EEG) has a long history as a clinical tool to study brain function, and its potential to derive biomarkers for various applications is far from exhausted. Machine learning (ML) can guide future innovation by harnes...

Reliable estimation of tree branch lengths using deep neural networks.

PLoS computational biology
A phylogenetic tree represents hypothesized evolutionary history for a set of taxa. Besides the branching patterns (i.e., tree topology), phylogenies contain information about the evolutionary distances (i.e. branch lengths) between all taxa in the t...

Lesion-Decoupling-Based Segmentation With Large-Scale Colon and Esophageal Datasets for Early Cancer Diagnosis.

IEEE transactions on neural networks and learning systems
Lesions of early cancers often show flat, small, and isochromatic characteristics in medical endoscopy images, which are difficult to be captured. By analyzing the differences between the internal and external features of the lesion area, we propose ...

Meta Learning With Graph Attention Networks for Low-Data Drug Discovery.

IEEE transactions on neural networks and learning systems
Finding candidate molecules with favorable pharmacological activity, low toxicity, and proper pharmacokinetic properties is an important task in drug discovery. Deep neural networks have made impressive progress in accelerating and improving drug dis...

Dynamic Loss Weighting for Multiorgan Segmentation in Medical Images.

IEEE transactions on neural networks and learning systems
Deep neural networks often suffer from performance inconsistency for multiorgan segmentation in medical images; some organs are segmented far worse than others. The main reason might be organs with different levels of learning difficulty for segmenta...

Repetitive Impedance Learning-Based Physically Human-Robot Interactive Control.

IEEE transactions on neural networks and learning systems
Model-based impedance learning control can provide variable impedance regulation for robots through online impedance learning without interaction force sensing. However, the existing related results only guarantee the closed-loop control systems to b...