AIMC Topic: Humans

Clear Filters Showing 7141 to 7150 of 95995 articles

Systematic Review: Use of Artificial Intelligence and Unmet Needs in Eosinophilic Oesophagitis.

Alimentary pharmacology & therapeutics
BACKGROUND: Artificial intelligence (AI) has been applied extensively to eosinophilic oesophagitis (EoE), but its clinical impact and comprehensiveness remain unclear.

The latest advances with natural products in drug discovery and opportunities for the future: a 2025 update.

Expert opinion on drug discovery
INTRODUCTION: The landscape of drug discovery is rapidly evolving, with natural products (NPs) playing a pivotal role in the development of novel therapeutics. Despite their historical significance, challenges persist in fully harnessing their potent...

The Current State of Artificial Intelligence on Detecting Pulmonary Embolism via Computerised Tomography Pulmonary Angiogram: A Systematic Review.

British journal of hospital medicine (London, England : 2005)
Pulmonary embolism (PE) is a life-threatening condition with significant diagnostic challenges due to high rates of missed or delayed detection. Computed tomography pulmonary angiography (CTPA) is the current standard for diagnosing PE, however, dem...

MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Journal of chemical information and modeling
Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing splicing, mRNA structure, translation efficiency, and other molecular mechanisms. Although driver synonymous mutations are significantly outnumbered by ...

MTGNN: A Drug-Target-Disease Triplet Association Prediction Model Based on Multimodal Heterogeneous Graph Neural Networks and Direction-Aware Metapaths.

Journal of chemical information and modeling
The forecasting of drug-target interactions (DTIs) is a crucial element in the domain of drug repositioning. Current methodologies, primarily based on dual-branch architectures or graph neural networks (GNNs), typically model binary associations─spec...

Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.

Journal of chemical information and modeling
Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learning models have advanced drug discovery, there remains a lack of generative frameworks for covalent ...

scGANSL: Graph Attention Network with Subspace Learning for scRNA-seq Data Clustering.

Journal of chemical information and modeling
Single-cell RNA sequencing (scRNA-seq) has become a crucial technology for analyzing cellular diversity at the single-cell level. Cell clustering is crucial in scRNA-seq data analysis as it accurately identifies distinct cell types and uncovers poten...

Chemical Properties-Based Deep Learning Models for Recommending Rational Daily Diet Combinations to Diabetics Through Large-Scale Virtual Screening of α-Glucosidase Dietary-Derived Inhibitors and Verified In Vitro.

Journal of agricultural and food chemistry
The lack of suitable chemical research methodologies has hindered the discovery of rational daily diet combinations from large-scale dietary-derived compounds. Three deep learning models based on chemical properties for α-glucosidase inhibitors (AGIs...

Effects of the lumbar support function of wearable robot (Bot Fit) on sitting position.

Biomedical engineering online
BACKGROUND: Sedentary lifestyles can lead to musculoskeletal disorders, but proper sitting posture, particularly maintaining a slight anterior pelvic tilt, helps prevent issues like lower back pain and spinal misalignment. Samsung Electronics wearabl...

Artificial intelligence-based detection of dens invaginatus in panoramic radiographs.

BMC oral health
OBJECTIVE: The aim of this study was to automatically detect teeth with dens invaginatus (DI) in panoramic radiographs using deep learning algorithms and to compare the success of the algorithms.