Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 63,261 to 63,270 of 230,760 articles

DSA-Diff: Dynamic schedule alignment for training-Inference consistent modality translation in x-prediction diffusion model.

Neural networks : the official journal of the International Neural Network Society
For modality translation tasks, diffusion models based on x-prediction offer faster and more accurate image generation compared to traditional ϵ-prediction. However, they often suffer from training-inference inconsistency (TII), which arises from a m... read more 

Small-molecule fluorescent probes for the aminergic GPCRs - What new tool compounds do we have post-2014 and what can they do?

European journal of medicinal chemistry
Aminergic G protein-coupled receptors (GPCRs) are heavily involved in the physiological functions of the human body and represent prominent drug targets for numerous diseases. Despite extensive work over the years, knowledge gaps persist as not all a... read more 

Adversarial contrastive with leveraging negative knowledge for point of interest sequence learning.

Neural networks : the official journal of the International Neural Network Society
The core of mining point of interest (POI) data is to learn the user preference representation. However, existing POI sequence learning methods often serve downstream tasks in an end-to-end manner. It lacks the ability to support multiple downstream ... read more 

The utility of artificial intelligence in plain language writing: A scoping review.

Patient education and counseling
BACKGROUND/PURPOSE: The prevalence of medical and technical jargon makes the dissemination of healthcare information to patients challenging. Plain language (PL) writing, a style of written communication that strives to employ clear and concise langu... read more 

G2CL: Gradient-guided graph contrastive learning for eliminating the message contrastive conflict.

Neural networks : the official journal of the International Neural Network Society
Graph contrastive learning methods based on the information noise contrastive estimation (InfoNCE) loss have made significant advances in graph representation learning. However, existing methods primarily focus on optimizing graph augmentation strate... read more 

Comparative analysis of machine learning algorithms for predicting stereotactic coordinates of the centromedian nucleus.

Journal of neurosurgery
OBJECTIVE: Deep brain stimulation (DBS) of the centromedian nucleus (CM) of the thalamus is a promising treatment for drug-resistant epilepsy, Tourette syndrome, disorders of consciousness, and chronic pain, particularly when other surgical options a... read more 

PANTHER Score: Protein-Affinity for Nucleic Target-binding, Hybridization, and Energy Regression.

RNA (New York, N.Y.)
Although protein-RNA interactions are crucial for many biological processes, predicting their binding free energies (ΔG) is a challenging task due to limited available experimental data and the complexity of these interactions. To address this issue,... read more 

The SynMall resource for characterizing the functional impact of synonymous variation.

Genome research
Synonymous single-nucleotide variants (sSNVs) are increasingly recognized as contributors to disease, yet existing variant annotation databases offer limited functional insights for sSNVs. Here, we present SynMall, a comprehensive resource designed t... read more 

Artificial Intelligence-Assisted Clinical Decision Model for Managing Retained Second Deciduous Molars With No Permanent Successors.

Orthodontics & craniofacial research
INTRODUCTION: The aim of this study was to develop and apply an artificial intelligence (AI) algorithm to aid the clinical decision-making process for managing mandibular retained second deciduous molars (SDM) with no permanent successors using machi... read more 

Multisequence MRI Enables High-Fidelity FDG-PET Synthesis for Epilepsy Using GANs.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure. PURPOSE: To evaluate synthetic FDG-PET generated from T1-weighted imaging and resting-state fMRI metrics. STUDY TYPE: Retrospective. POPULATION:... read more