AIMC Topic: Neural Networks, Computer

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Integrating Retinal Segmentation Metrics with Machine Learning for Predictions from Mouse SD-OCT Scans.

Current eye research
PURPOSE: This study aimed to initially test whether machine learning approaches could categorically predict two simple biological features, mouse age and mouse species, using the retinal segmentation metrics.

MSMDL-DDI: Multi-Layer Soft Mask Dual-View Learning for Drug-Drug Interactions.

Computational biology and chemistry
Drug-drug interactions (DDIs) occur when multiple medications are co-administered, potentially leading to adverse effects and compromising patient safety. However, existing DDI prediction methods often overlook the intricate interactions among chemic...

Application-driven validation of posteriors in inverse problems.

Medical image analysis
Current deep learning-based solutions for image analysis tasks are commonly incapable of handling problems to which multiple different plausible solutions exist. In response, posterior-based methods such as conditional Diffusion Models and Invertible...

Monkeypox diagnosis based on probabilistic K-nearest neighbors (PKNN) algorithm.

Computers in biology and medicine
Although it is not a new illness and has been around since the previous century, monkeypox later resurgence is fraught with difficulties. This study presents a novel approach of diagnosing monkeypox using artificial intelligence, which is called Effe...

DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation.

International journal of computer assisted radiology and surgery
PURPOSE: Semantic segmentation and landmark detection are fundamental tasks of medical image processing, facilitating further analysis of anatomical objects. Although deep learning-based pixel-wise classification has set a new-state-of-the-art for se...

A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography.

NeuroImage
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are pr...

Prediction of coffee traits by artificial neural networks and laser-assisted rapid evaporative ionization mass spectrometry.

Food research international (Ottawa, Ont.)
BACKGROUND: Coffee is an important commodity in the worldwide economy and smart technologies are important for accurate quality control and consumer-oriented product development. Sensory perception is probably the most important information since it ...

Mapping the topography of spatial gene expression with interpretable deep learning.

Nature methods
Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of these data complicates analysis of spatial gene expression patterns. We address this issue by deriving a to...

Analysis of Cardiac Arrhythmias Based on ResNet-ICBAM-2DCNN Dual-Channel Feature Fusion.

Sensors (Basel, Switzerland)
Cardiovascular disease (CVD) poses a significant challenge to global health, with cardiac arrhythmia representing one of its most prevalent manifestations. The timely and precise classification of arrhythmias is critical for the effective management ...

Low-Cost Raman Spectroscopy Setup Combined with a Machine Learning Model.

Sensors (Basel, Switzerland)
The diagnosis of kidney diseases presents significant challenges, including the reliance on variable and unstable biomarkers and the necessity for complex and expensive laboratory tests. Raman spectroscopy emerges as a promising technique for analyzi...