Artificial Intelligence Medical Compendium

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

Showing 33,651 to 33,660 of 221,422 articles

Face-like holistic processing in non-face stimuli.

Cognitive psychology
Holistic processing of visual stimuli has long been regarded as unique to faces, or otherwise extended to other object categories given sufficient expertise. We designed novel abstract stimuli that are recognizable strictly by configural information,... read more 

Integrative assessment of sulfoxaflor effects on gene expression, reproduction, and behavior in the bumblebee Bombus impatiens.

Ecotoxicology and environmental safety
Social insect pollinators, such as bumblebees, face increasing threats from environmental agrochemicals; yet the sublethal effects of these compounds across different levels of biological organization remain poorly understood. This study uses an inte... read more 

Why we need to maintain a critical view on big data and artificial intelligence predictions.

Current opinion in immunology
Artificial intelligence (AI) and machine learning are widely promoted as transformative tools for medical practice, yet their impact in daily rheumatology remains limited. This review examines the gap between expectations and reality using historical... read more 

Machine learning-based clustering differentiates bilateral hepatocellular carcinoma characteristics and prognosis.

Surgery
BACKGROUND: Bilateral hepatocellular carcinoma represents a biologically heterogeneous disease with uncertain optimal surgical selection criteria. Although hepatic resection can provide survival benefit in selected patients, outcomes remain variable,... read more 

Point2SSM++: Self-supervised learning of anatomical shape models from point clouds.

Medical image analysis
Correspondence-based statistical shape modeling (SSM) stands as a powerful technology for morphometric analysis in clinical research. SSM facilitates population-level characterization and quantification of anatomical shapes such as bones and organs, ... read more 

Artificial intelligence in emergency nursing: A scoping review of applications and implications.

International emergency nursing
INTRODUCTION: Artificial intelligence (AI) has advanced rapidly in healthcare; however, its application in emergency nursing remains underexplored. This study aimed to map and synthesise existing evidence to clarify current applications, gaps, and pr... read more 

Linking rare variants to cell-type function in profound autism with brain transcriptomics and foundation models.

Cell genomics
Genetic association studies have identified numerous genes harboring protein-disrupting variants in individuals with profound autism, but identifying convergent points of vulnerability remains challenging. We discuss how brain transcriptomic resource... read more 

A simulation-based study of 3D printing angle optimization by integrating deep learning and NSGA-III for prosthesis and retainer manufacturing.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Current dental 3-dimensional (3D) printing workflows lack automated tools for optimizing build orientations that preserve critical clinical surfaces. Existing slicing software programs often require manual adjustment and may pla... read more 

Artificial Intelligence in Personalized Breast Cancer Drug Safety: From Preclinical Toxicology to Clinical Risk Management.

Clinical therapeutics
PURPOSE: The artificial intelligence (AI) implementation in personalized medicine has transformed drug safety, especially in breast cancer treatment. The importance of the need to treat breast cancer individually is acute as the disorder is heterogen... read more 

Multiparametric MRI-Based Integrated Analysis of Clinical, Radiomics, Deep Learning, and Machine Learning for Predicting Tumor Proliferation and Prognosis in Locally Advanced Rectal Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: This study aimed to develop and validate a predictive model integrating clinical, radiomics, deep learning (DL), and machine learning (ML) from multiparametric magnetic resonance imaging (MRI) for predicting tumor cell proli... read more