AIMC Topic: Algorithms

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Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms.

Frontiers in immunology
BACKGROUND: In the face of continued growth in the elderly population, the need to understand and combat age-related cardiac decline becomes even more urgent, requiring us to uncover new pathological and cardioprotective pathways.

PERform: assessing model performance with predictivity and explainability readiness formula.

Journal of environmental science and health. Part C, Toxicology and carcinogenesis
In the rapidly evolving field of artificial intelligence (AI), explainability has been traditionally assessed in a post-modeling process and is often subjective. In contrary, many quantitative metrics have been routinely used to assess a model's perf...

Text mining of hypertension researches in the west Asia region: a 12-year trend analysis.

Renal failure
More than half of the world population lives in Asia and hypertension (HTN) is the most prevalent risk factor found in Asia. There are numerous articles published about HTN in Eastern Mediterranean Region (EMRO) and artificial intelligence (AI) metho...

Unsupervised Bidirectional Contrastive Reconstruction and Adaptive Fine-Grained Channel Attention Networks for image dehazing.

Neural networks : the official journal of the International Neural Network Society
Recently, Unsupervised algorithms has achieved remarkable performance in image dehazing. However, the CycleGAN framework can lead to confusion in generator learning due to inconsistent data distributions, and the DisentGAN framework lacks effective c...

Unsupervised model adaptation for source-free segmentation of medical images.

Medical image analysis
The recent prevalence of deep neural networks has led semantic segmentation networks to achieve human-level performance in the medical field, provided they are given sufficient training data. However, these networks often fail to generalize when task...

HRU-Net: A high-resolution convolutional neural network for esophageal cancer radiotherapy target segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The effective segmentation of esophageal squamous carcinoma lesions in CT scans is significant for auxiliary diagnosis and treatment. However, accurate lesion segmentation is still a challenging task due to the irregular for...

DEEP-EP: Identification of epigenetic protein by ensemble residual convolutional neural network for drug discovery.

Methods (San Diego, Calif.)
Epigenetic proteins (EP) play a role in the progression of a wide range of diseases, including autoimmune disorders, neurological disorders, and cancer. Recognizing their different functions has prompted researchers to investigate them as potential t...

Human Action Recognition and Note Recognition: A Deep Learning Approach Using STA-GCN.

Sensors (Basel, Switzerland)
Human action recognition (HAR) is growing in machine learning with a wide range of applications. One challenging aspect of HAR is recognizing human actions while playing music, further complicated by the need to recognize the musical notes being play...

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.

Magma (New York, N.Y.)
PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete sc...

Entropy-Weighted Numerical Gradient Optimization Spiking Neural System for Biped Robot Control.

International journal of neural systems
The optimization of robot controller parameters is a crucial task for enhancing robot performance, yet it often presents challenges due to the complexity of multi-objective, multi-dimensional multi-parameter optimization. This paper introduces a nove...