AIMC Topic: Deep Learning

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Multimodal depression recognition and analysis: Facial expression and body posture changes via emotional stimuli.

Journal of affective disorders
BACKGROUND: Clinical studies have shown that facial expressions and body posture in depressed patients differ significantly from those of healthy individuals. Combining relevant behavioral features with artificial intelligence technology can effectiv...

Artificial intelligence in bacterial diagnostics and antimicrobial susceptibility testing: Current advances and future prospects.

Biosensors & bioelectronics
Recently, artificial intelligence (AI) has emerged as a transformative tool, enhancing the speed, accuracy, and scalability of bacterial diagnostics. This review explores the role of AI in revolutionizing bacterial detection and antimicrobial suscept...

Applying deep learning algorithms for non-invasive estimation of carotenoid content in the foot muscle of Pacific abalone with different colors.

Food chemistry
Carotenoids are vital pigments influencing both the coloration and health of aquatic organisms, particularly in species such as the Pacific abalone (Haliotis discus hannai). In this study, we identified the major carotenoids in abalone foot muscle us...

A Diagnosis-Based Siamese Network for Fault Detection Through Transfer Learning.

Journal of chemical information and modeling
Traditional deep-learning-based approaches often struggle with data imbalance and variability across fault conditions and normal scenarios, especially in industrial processes. Besides, inconsistent feature distributions from combining different fault...

DeepPSA: A Geometric Deep Learning Model for PROTAC Synthetic Accessibility Prediction.

Journal of chemical information and modeling
Proteolysis-targeting chimeras (PROTACs) have garnered significant attention in drug design due to their ability to induce the degradation of the target proteins via the ubiquitin-proteasome system. However, the synthesis of PROTACs remains a challen...

Dual-Branch Contrastive Network with Deep Separable Convolution for Enhanced 6mA Site Identification.

Journal of chemical information and modeling
DNA N6-methyladenine (6mA) is a pivotal DNA modification integral to various biological processes, yet its exact regulatory role in eukaryotes is still unclear and controversial due to its sparsity, limitations in detection technologies, and complex ...

Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning.

Journal of chemical information and modeling
The versatility of multimodal deep learning holds tremendous promise for advancing scientific research and practical applications. As this field continues to evolve, the collective power of cross-modal analysis promises to drive transformative innova...

Transfer-Learning Deep Raman Models Using Semiempirical Quantum Chemistry.

Journal of chemical information and modeling
Biophotonic technologies such as Raman spectroscopy are powerful tools for obtaining highly specific molecular information. Due to its minimal sample preparation requirements, Raman spectroscopy is widely used across diverse scientific disciplines, o...

BalancedDiff: Balanced Diffusion Network for High-Quality Molecule Generation.

Journal of chemical information and modeling
Traditional drug discovery and development are time-consuming and expensive. Deep learning-based molecule generation techniques can reduce costs and improve efficiency, helping to generate high-quality molecules with desirable properties. However, ex...

A Hyperbolic Discrete Diffusion 3D RNA Inverse Folding Model for Functional RNA Design.

Journal of chemical information and modeling
Generative design of functional RNAs presents revolutionary opportunities for diverse RNA-based biotechnologies and biomedical applications. To this end, RNA inverse folding is a promising strategy for generatively designing new RNA sequences that ca...