Artificial Intelligence Medical Compendium

OBJECTIVE: To externally validate the accuracy of deep learning-based iliac artery tortuosity assessment (PRAEVAorta 2, Bordeaux, France) in computed tomography angiography of patients with abdominal aortic aneurysms. DESIGN: Retrospective, multi-cen... read more 

Fourier transform infrared (FTIR) spectroscopy is often used in forensic science due to its ability to obtain a (bio-)chemical fingerprint of the sample. This method could also be used in forensic entomology to obtain additional information about emp... read more 

The formation patterns of heterocyclic amines (HAs), carcinogens formed during meat cooking, in real food matrices remain incompletely understood. This study developed generalized kinetic and machine learning (ML) models to characterize bound and fre... read more 

Artificial intelligence (AI) is increasingly used in reproductive endocrinology and infertility (REI), influencing nearly all aspects of assisted reproduction. Reported applications include ovarian stimulation, gamete and embryo assessment, endometri... read more 

Inflammatory bowel diseases (IBD) present significant diagnostic and therapeutic challenges due to their heterogeneity. Here, we analyze exhaled volatile organic compounds (VOCs) from 244 individuals, uncovering distinct metabolic signatures associat... read more 

AIM: Irreversible pulpitis poses a significant clinical burden due to progressive inflammatory pulp damage. While inflammatory mechanisms are central to its pathogenesis, they remain incompletely characterised. This study aims to elucidate the role o... read more 

Open-shell systems such as radical intermediates are central to radical polymerization (RP), combustion, catalysis, and many other chemical and industrial processes, yet their accurate modeling presents significant computational challenges. Most of t... read more 

BACKGROUND: Post-stroke dysphagia (PSD) significantly increases the risk of aspiration-related pneumonia. While prior studies have linked abnormal temporal coordination of swallowing motions to aspiration, limited efforts have been made to explore it... read more 

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Mold identification in clinical diagnostics is traditionally labor-intensive and is dependent on expert interpretation. MoldVision is a deep-learning approach that uses smartphone images of mold cultures to automate identification. We analyzed 161 cl... read more