AI Medical Compendium

Clinical outcomes and predictors of response to PD-(L)1 blockade in patients with NSCLC without actionable genomic alterations who never used tobacco.

Clinical cancer research : an official journal of the American Association for Cancer Research May 18, 2026

PURPOSE: Predictive biomarkers of response to immune checkpoint inhibitors (ICI) remain poorly defined in patients with non-small cell lung cancer (NSCLC) without a history of tobacco use and lacking actionable genomic alterations (AGA). We aimed to ... read more

Characterizing Airborne Particulate Matter During Late-Season Soybean Production Using SEM/EDX Automated Single Particle Analyses and Machine Learning: A Preliminary Study in the Mississippi Delta.

Bulletin of environmental contamination and toxicology May 18, 2026

Airborne particulate matter (PM) may originate from exposed agricultural fields and activities during dry periods. A preliminary study assessed sources of airborne PM in 2023, starting two weeks before soybean harvest. Three passive samplers were pla... read more

Beyond gross total resection (GTR): Deep peritumoral radiomics for predicting overall survival (OS) and O6-methylguanine-DNA-methyltransferase promoter methylation (MGMTpm) status in glioblastoma multiforme.

Neuroradiology May 18, 2026

BACKGROUND & OBJECTIVE: Glioblastoma Multiforme (GBM) is an aggressive and highly heterogeneous brain tumor with poor survival outcomes. While conventional radiomic analyses focus on tumor-centric regions, emerging surgical strategies, such as GTR an... read more

Peptides as integrative modulators for clinical prognosis and targeted therapy in pancreatic cancer.

Discover oncology May 18, 2026

Pancreatic cancer remains a formidable global health challenge, ranking as the twelfth most common malignancy yet claiming an outsized toll with dismal 5-year survival rates 13.3%, largely due to late-stage diagnosis and limited therapeutic options. ... read more

Air pollution-related health impacts from domestic waste burning and associated interventions: the merits of a traditional versus machine learning scoping review methodology.

Environmental monitoring and assessment May 18, 2026

Regularly updating repositories of air pollution impacts on health is essential for evidence-based policies, interventions, and progress monitoring. However, this is often time-consuming and labour-intensive. Automation can ensure up-to-date evidence... read more

Unraveling Atherosclerosis through Multi-omics: Systematic Insights into the Unique Applications and Clinical Perspectives.

Current atherosclerosis reports May 18, 2026

PURPOSE OF REVIEW: Atherosclerosis (AS) is a progressive disease of the arterial wall characterized by metabolic dysregulation, inflammatory activation, and genetic susceptibility. Given the complex interactions across molecular layers, this review a... read more

Artificial intelligence for risk-stratified breast cancer screening: a systematic review of evidence, clinical integration, and ethical implications in risk assessment tools.

La Radiologia medica May 18, 2026

BACKGROUND: Conventional age-based breast cancer screening ignores substantial inter-individual risk variation, contributing to overdiagnosis, false positives, and missed opportunities for earlier detection in high-risk women. Mammography-based artif... read more

Single-cell profiling and machine learning identify cuproptosis-related fibroblast subpopulations and fibrogenesis modulator AEBP1 in endometriosis.

Apoptosis : an international journal on programmed cell death May 18, 2026

Endometriosis is characterized by progressive fibrosis and limited therapeutic options. Cuproptosis, a copper-dependent form of regulated cell death, has been implicated in multiple pathological conditions, but its relevance to fibroblast-mediated fi... read more

Prediction of venous thromboembolism after spontaneous intracerebral hemorrhage based on machine learning.

Journal of thrombosis and thrombolysis May 18, 2026

Patients with intracerebral hemorrhage (ICH) are at high risk of venous thromboembolism (VTE). Current risk assessment tools are limited and not tailored for neurocritical care populations. This study aimed to develop and validate machine learning-ba... read more

Artificial neural network optimization of gyrotactic microbes in water hybrid nanoliquid with carbon nanotubes using modified Hamilton crosser model.

Discover nano May 18, 2026

The artificial neural network-optimized model for exploring local thermal non-equilibrium (LTNE) influences on gyrotactic microorganisms in a chemically reactive SWCNTs-MWCNTs/water-based hybrid nanofluid has a wide range of applications in advanced ... read more

Artificial Intelligence Medical Compendium