AIMC Topic: Algorithms

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Ag@CDS SERS substrate coupled with lineshape correction algorithm and BP neural network to detect thiram in beverages.

Talanta
Surface enhanced Raman scattering (SERS) has been proved an effective analytical technique due to its high sensitivity, however, how to identify and extract useful information from raw SERS spectra is still a problem that needs to be resolved. In thi...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

International journal of legal medicine
Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and this issue has yet to be conclusively resolved. The advantages of objectivity and non-invasiveness make computing tomography (CT) imaging an potential ...

Reconsidering learnable fine-grained text prompts for few-shot anomaly detection in visual-language models.

Neural networks : the official journal of the International Neural Network Society
Few-Shot Anomaly Detection (FSAD) in industrial images aims to identify abnormalities using only a few normal images, which is crucial for industrial scenarios where sample training is limited. The recent advances in large-scale pre-trained visual-la...

Diminishing spectral bias in physics-informed neural networks using spatially-adaptive Fourier feature encoding.

Neural networks : the official journal of the International Neural Network Society
Physics-informed neural networks (PINNs) have recently emerged as a promising framework for solving partial differential equation (PDE) systems in computer mechanics. However, PINNs still struggle in simulating systems whose solution functions exhibi...

Artificial intelligence in assessing progression of age-related macular degeneration.

Eye (London, England)
The human population is steadily growing with increased life expectancy, impacting the prevalence of age-dependent diseases, including age-related macular degeneration (AMD). Health care systems are confronted with an increasing burden with rising pa...

MMD-Net: Image domain multi-material decomposition network for dual-energy CT imaging.

Medical physics
BACKGROUND: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.

Overcoming the preferred-orientation problem in cryo-EM with self-supervised deep learning.

Nature methods
While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing ...

Predicting Asthma Exacerbations Using Machine Learning Models.

Advances in therapy
INTRODUCTION: Although clinical, functional, and biomarker data predict asthma exacerbations, newer approaches providing high accuracy of prognosis are needed for real-world decision-making in asthma. Machine learning (ML) leverages mathematical and ...

Prediction and Elimination of Physiological Tremor During Control of Teleoperated Robot Based on Deep Learning.

Sensors (Basel, Switzerland)
Currently, teleoperated robots, with the operator's input, can fully perceive unknown factors in a complex environment and have strong environmental interaction and perception abilities. However, physiological tremors in the human hand can seriously ...

Convergence of Nanotechnology and Machine Learning: The State of the Art, Challenges, and Perspectives.

International journal of molecular sciences
Nanotechnology and machine learning (ML) are rapidly emerging fields with numerous real-world applications in medicine, materials science, computer engineering, and data processing. ML enhances nanotechnology by facilitating the processing of dataset...