AI Medical Compendium

Screening for Periodontitis Using Blood Biomarkers and Demographic Data: A Machine Learning Study.

Oral health & preventive dentistry May 20, 2026

PURPOSE: Periodontitis is a common chronic disease associated with systemic conditions such as diabetes and cardiovascular disease. Diagnosis typically relies on dental examinations and radiographs, which may be underutilised by individuals who avoid... read more

Contrastive graph regularized non-negative matrix factorization for domain identification of spatial transcriptomics.

Journal of the Royal Society, Interface May 20, 2026

Spatial transcriptomics captures gene expression with spatial resolution, but its high dimensionality complicates spatial domain identification. While deep learning excels in feature extraction, its limited interpretability underscores the need for d... read more

A translational multimodal machine-learning prototype predicting valproate response in epilepsy treatment.

Epilepsia May 20, 2026

OBJECTIVE: Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first-line ASM, yet only approximately half of patients achieve sustained seizure ... read more

Deep Learning Analysis of Indocyanine Green Fluoroscopy of Ureters in Robotic Cystectomy: Toward Reducing Ureteroenteric Strictures.

Journal of endourology May 20, 2026

OBJECTIVES: To develop a deep learning method to quantify ureter perfusion during indocyanine green (ICG) fluoroscopy in robot-assisted radical cystectomy (RARC). INTRODUCTION: Ureteroenteric stricture (UES) is a common and clinically significant com... read more

A Machine Learning Approach to Understand Thermal Desorption Profiles of Levoglucosan from FIGAERO-CIMS.

Environmental science & technology May 20, 2026

The Filter Inlet for Gases and AEROsols coupled to a Chemical Ionization Mass Spectrometer (FIGAERO-CIMS) can be used to derive volatility of atmospheric aerosol by using the temperature at thermogram maximum signal (Tmax). For complex ambient partic... read more

Using a large language model as a third reviewer to augment dual human full-text screening in orthopaedic systematic reviews.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA May 20, 2026

PURPOSE: Large language models (LLMs) are a form of artificial intelligence (AI) that have emerged as potential tools to augment systematic review workflows. This study aimed to evaluate GPT-5 as a third reviewer for full-text screening across orthop... read more

From patient notes to prognostication: The revolutionary potential of event-based foundation models in orthopaedics.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA May 20, 2026

The integration of artificial intelligence (AI)-equipped tools into electronic health record (EHR) platforms may drive the evolution of orthopaedic diagnosis and decision-making, leveraging big data to generate precise and context-aware insights. Wit... read more

QSAR in the AI Era: Reflections for Advancing Chemical Safety Assessment.

Chemical research in toxicology May 20, 2026

Quantitative Structure-Activity Relationship (QSAR) models are increasingly discussed in the broader context of artificial intelligence (AI). Indeed, they formally meet certain regulatory definitions of AI as data-driven inference systems. However, i... read more

Automated scoring of student videos in medical education: a comparison between a large language model and expert evaluation.

Journal of microbiology & biology education May 20, 2026

Video-based assignments are used in medical education, yet expert scoring is time-intensive. Large language models (LLMs) offer scalable alternatives, but their validity for evaluating multimodal student work is uncertain. We examined whether a state... read more

Development and Validation of a Deep Learning-enabled Single Breath-hold Abbreviated MRI Protocol for Hepatocellular Carcinoma Diagnosis.

Radiology. Artificial intelligence May 20, 2026

Purpose To develop a deep learning-enabled single breath-hold abbreviated MRI (DL-SBH-aMRI) protocol for hepatocellular carcinoma (HCC) diagnosis. Materials and Methods Patients at high risk of HCC from four institutions (January 2019-January 2025) w... read more

Artificial Intelligence Medical Compendium