AI Medical Compendium

Three-dimensional oxygen maps of tumors in real time - Analysis in the context of active tumor vasculature.

Computer methods and programs in biomedicine Apr 23, 2026

BACKGROUND AND OBJECTIVE: Characterizing the tumor microenvironment (TME) requires integrating multiple physiological features, including oxygenation, vascularity, and redox status. While EPR oxygen imaging (EPROI) provides spatial pO₂ maps, conventi... read more

Depth map filtering method for shape-from-focus recovery based on hybrid network model.

Micron (Oxford, England : 1993) Apr 23, 2026

Shape-from-focus (SFF) is an economically efficient 3D shape recovery technology. As a core module of 3D digital microscopes, its primary goal is to acquire high-quality depth maps. However, the performance of such technology is highly dependent on t... read more

Comparative Evaluation of Deep Learning Models for 3D Segmentation and Volumetry of Vestibular Schwannomas Using Large Heterogeneous Data Sets with External Validation.

AJNR. American journal of neuroradiology Apr 23, 2026

BACKGROUND AND PURPOSE: 3D segmentation and volumetry of vestibular schwannomas (VSs) is a more accurate method to determine tumor growth on serial imaging, but manual annotation is time-consuming to implement in routine clinical practice. We evaluat... read more

Deep-Learning Accelerated Vessel Wall Imaging Using T1-SPACE at Ultra-High-Field Strength MRI.

AJNR. American journal of neuroradiology Apr 23, 2026

BACKGROUND AND PURPOSE: Current literature on deep learning-accelerated intracranial vessel wall imaging has been largely limited to postprocessing-based approaches at 3T, with comparatively sparse data at 7T. The purpose of the present study was to ... read more

Multimodal artificial intelligence for retinal detachment diagnosis using fundus imaging and patient questionnaires.

The British journal of ophthalmology Apr 22, 2026

BACKGROUND/AIMS: This study aimed to develop a multimodal artificial intelligence (AI) system that integrates fundus imaging and patient questionnaire data to achieve clinician-level diagnostic accuracy for diagnosing retinal detachment (RD). METHODS... read more

In silico metabolite prediction and LC-HRMS confirmation for forensic analysis of a fatal case involving novel synthetic opioid N, N-dimethyl etonitazene.

Journal of analytical toxicology Apr 22, 2026

Nitazenes are a class of new psychoactive substances (NPS) belonging to the synthetic opioids. It has potent μ-opioid receptor agonist activity. In this study, we investigated an authentic forensic human blood and urine sample from an individual that... read more

Delineating Pediatric Adrenocortical Tumors by GC-MS Urinary Steroid Metabolome Analysis: Observations From the MET Study.

The Journal of clinical endocrinology and metabolism Apr 22, 2026

INTRODUCTION: Adrenocortical tumors (ACTs) comprise adrenocortical adenomas (ACAs) and adrenocortical carcinomas (ACCs); the latter are highly aggressive. Pediatric adrenocortical tumors (pACTs) are functional and thus symptomatic. We investigated wh... read more

Breath-hold CBCT-to-CT synthesis using an unsupervised artifact disentanglement network with Mamba for breast cancer adaptive radiotherapy.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine Apr 22, 2026

BACKGROUND: Accurate and up-to-date anatomical information is critical for effective treatment planning in breast cancer adaptive radiotherapy. Cone-beam computed tomography facilitates real-time plan optimization but lacks sufficient electron densit... read more

Screening of metabolic-related biomarkers linking intervertebral disc degeneration and type 2 diabetes based on comprehensive bioinformatics analysis and machine learning.

Biochemistry and biophysics reports Apr 22, 2026

BACKGROUND: Intervertebral disc degeneration (IVDD) is a prominent etiology of lower back pain. Type 2 diabetes (T2D), the most prevalent metabolic disorder, may expedite IVDD progression through mechanisms involving hyperglycemia, advanced glycation... read more

Accuracy of machine learning models for mitral regurgitation severity assessment: A systematic review and meta-analysis.

International journal of cardiology. Cardiovascular risk and prevention Apr 22, 2026

BACKGROUND: Accurate assessment of mitral regurgitation (MR) severity is crucial for guiding clinical management, but is often limited by the subjectivity and variability of traditional echocardiographic evaluations. Machine learning (ML) models offe... read more

Artificial Intelligence Medical Compendium