AI Medical Compendium

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Experimental & molecular medicine May 8, 2026

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatments such as neoadjuvant chemotherapy (NAC). Although transcriptome profiling has shown differences i... read more

De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics.

Experimental & molecular medicine May 8, 2026

Growth differentiation factor-15 (GDF15), a stress-responsive cytokine of the transforming growth factor-β superfamily, is elevated in cancer cachexia, chemotherapy-induced nausea, and hyperemesis gravidarum, making it both a biomarker and a therapeu... read more

Artificial intelligence-assisted diagnosis and subtype differentiation of infectious keratitis.

Eye (London, England) May 8, 2026

BACKGROUND: Infectious keratitis (IK) is a major cause of corneal blindness world-wide, and prompt identification of IK and its etiologic subtype is essential for appropriate management. We developed deep learning (DL) models to detect IK and differe... read more

Consistency analysis of AI cell recognition results between non anticoagulant and anticoagulant marrow smear after Wright's staining.

Scientific reports May 8, 2026

The integration of artificial intelligence with bone marrow cytology represents a significant trend in the application of AI image recognition technology within the medical sector. Despite the current high accuracy of AI in cell identification, there... read more

From decision support to clinical integration: A scoping review of artificial intelligence in prehospital airway management.

International journal of medical informatics May 8, 2026

BACKGROUND: Airway management is a critical component of prehospital emergency care, where rapid decision-making and procedural accuracy are essential for patient survival. In recent years, artificial intelligence has emerged as a promising tool. How... read more

Brain-age defines a structural signature of outcomes after vagus nerve stimulation in children.

Brain stimulation May 8, 2026

INTRODUCTION: Outcomes following vagus nerve stimulation (VNS) are difficult to predict prior to surgery in pediatric drug-resistant epilepsy (DRE). We investigated whether structural brain differences among children may explain variability in VNS re... read more

Rapid Multi-Parametric Quantitative MRI via Deep Learning-Based Synthetic-to-Real Reconstruction and 3D SSFP-MOLED Imaging.

NeuroImage May 8, 2026

Multi-parametric quantitative magnetic resonance imaging (mqMRI) holds significant clinical potential through multi-parametric tissue characterization, yet its adoption is hindered by prolonged scan time and sensitivity to non-ideal signal conditions... read more

A Novel Wearables-Based Sleep Quality Index to Quantify Postoperative Sleep Quality.

The Journal of thoracic and cardiovascular surgery May 8, 2026

OBJECTIVE: To develop a novel wearables-based sleep index that can quantify sleep disruption after lung resection and to apply machine learning analysis to these indices to identify patients exhibiting distinct postoperative sleep patterns. METHODS: ... read more

Machine learning models in the prediction of adverse outcomes in peripheral arterial disease: meta-analysis.

Annals of vascular surgery May 8, 2026

OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the performance of machine learning (ML) models compared to traditional statistical approaches in predicting adverse outcomes for patients with peripheral arterial disease (PAD), w... read more

Development of Models for Predicting the 7-Month Risk of Venous Thromboembolism and Clinically Relevant Bleeding in Ambulatory Patients with Cancer: Analysis from the AVERT Trial.

Journal of thrombosis and haemostasis : JTH May 8, 2026

BACKGROUND: Patients with cancer are at elevated risk of venous thromboembolism (VTE). While primary thromboprophylaxis reduces VTE incidence, it also increases bleeding risk, necessitating accurate risk stratification. Existing tools (e.g., Khorana ... read more

Artificial Intelligence Medical Compendium