AIMC Topic: Deep Learning

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Quantitative analysis of ureteral jets with dynamic magnetic resonance imaging and a deep-learning approach.

Magnetic resonance imaging
OBJECTIVE: To develop dynamic MRU protocol that focuses on the bladder to capture ureteral jets and to automatically estimate frequency and duration of ureteral jets from the dynamic images.

Deep-learning analysis of greenspace and metabolic syndrome: A street-view and remote-sensing approach.

Environmental research
Evidence linking greenspace exposure to metabolic syndrome (MetS) remains sparse and inconsistent. This exploratory study evaluate the relationship between green visibility index (GVI) and normalized difference vegetation index (NDVI) with MetS preva...

Integrating local and global attention mechanisms for enhanced oral cancer detection and explainability.

Computers in biology and medicine
BACKGROUND AND OBJECTIVE: Early detection of Oral Squamous Cell Carcinoma (OSCC) improves survival rates, but traditional diagnostic methods often produce inconsistent results. This study introduces the Oral Cancer Attention Network (OCANet), a U-Net...

Female autism categorization using CNN based NeuroNet57 and ant colony optimization.

Computers in biology and medicine
Autism identification and classification using biomedical medical image analysis has advanced recently. Research shows autistic females have different phenotypic and age-related brain variations than males. Gender-specific hormones and genes affect a...

Automatic cerebral microbleeds detection from MR images via multi-channel and multi-scale CNNs.

Computers in biology and medicine
BACKGROUND: Computer-aided detection (CAD) systems have been widely used to assist medical professionals in interpreting medical images, aiding in the detection of potential diseases. Despite their usefulness, CAD systems cannot yet fully replace doc...

Multitask Deep Learning Models of Combined Industrial Absorption, Distribution, Metabolism, and Excretion Datasets to Improve Generalization.

Molecular pharmaceutics
The optimization of absorption, distribution, metabolism, and excretion (ADME) profiles of compounds is critical to the drug discovery process. As such, machine learning (ML) models for ADME are widely used for prioritizing the design and synthesis o...

SWAPS: A Modular Deep-Learning Empowered Peptide Identity Propagation Framework Beyond Match-Between-Run.

Journal of proteome research
Mass spectrometry (MS)-based proteomics relies heavily on MS/MS (MS2) data, which do not fully exploit the available MS1 information. Traditional peptide identity propagation (PIP) methods, such as match-between-runs (MBR), are limited to similar run...

Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system.

Journal of environmental management
The escalating impacts of climate change have intensified extreme rainfall events, placing urban drainage systems under unprecedented pressure and increasing flood risks. Addressing these challenges requires advanced flood mitigation strategies, opti...

DeepMVD: A Novel Multiview Dynamic Feature Fusion Model for Accurate Protein Function Prediction.

Journal of chemical information and modeling
Proteins, as the fundamental macromolecules of life, play critical roles in various biological processes. Recent advancements in intelligent protein function prediction methods leverage sequences, structures, and biomedical literature data. Among the...

Classification of Mycena and Species Using Deep Learning Models: An Ecological and Taxonomic Approach.

Sensors (Basel, Switzerland)
Fungi play a critical role in ecosystems, contributing to biodiversity and providing economic and biotechnological value. In this study, we developed a novel deep learning-based framework for the classification of seven macrofungi species from the ge...