AI Medical Compendium

Evaluating artificial intelligence-generated synthesized mammography as a standalone alternative to digital mammography with or without tomosynthesis.

Japanese journal of radiology May 25, 2026

PURPOSE: To evaluate whether standalone synthesized mammography (SM) can maintain or improve diagnostic accuracy while reducing reading time and radiation dose, compared to digital breast tomosynthesis (DBT) with digital mammography (DM) or DM alone.... read more

Integrative transcriptomic and single-cell analysis reveals metabolic reprogramming and hexosamine biosynthesis-mediated tumor microenvironment remodeling in prostate cancer.

Discover oncology May 25, 2026

BACKGROUND: Prostate cancer is one of the most common malignancies in men and exhibits substantial clinical heterogeneity. A considerable proportion of patients experience biochemical recurrence after primary treatment, and metabolic reprogramming ha... read more

Optimizing Deep Learning for Renal Mass Characterization in Challenging Cases: A Comparative Study of Spatial-Input Strategies and a Validated ROI-Only DLR Nomogram.

Annals of surgical oncology May 25, 2026

PURPOSE: Our purpose was to develop and validate an integrated clinical deep learning radiomics (DLR) nomogram for differentiation of fat-poor angiomyolipoma (fp-AML) from clear-cell renal cell carcinoma (ccRCC) in diagnostically challenging cases an... read more

T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.

Archives of microbiology May 25, 2026

Influenza A viruses pose a significant pandemic threat, with H2N3 in particular representing a subtype of particular concern due to limited population immunity and potential for zoonotic transmission. Traditional antibody-centric vaccine strategies f... read more

A review of deep learning-based multimodal data integration of lung cancer.

Clinical and experimental medicine May 25, 2026

This is a narrative review that provides a perspective on the recent advances in deep learning (DL)-driven multimodal data integration for lung cancer. Lung cancer remains the most prevalent malignancy and the leading cause of cancer-related mortalit... read more

Advances in quantum dot-based fluorescent biosensors for enzyme detection: mechanistic insights and applications in disease.

Mikrochimica acta May 25, 2026

It is imperative to develop precise detection tools for enzymes, as key biomarkers in disease pathogenesis, to fuel progress in clinical diagnostics and personalized medicine. Quantum dots (QDs), with exceptional photostability, size-tunable emission... read more

Comparison of human vs AI-generated feedback: results from an online survey study in the GlomCon glomerular disease fellowship program.

Journal of nephrology May 25, 2026

Optimizing Renal Fibrosis Assessment in Patients with Chronic Kidney Disease: Feature and Decision-Level Fusion in Machine Learning Using Clinical and Ultrasound Information.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine May 25, 2026

PURPOSE: Machine learning has been extensively applied in nephrology. This study aims to evaluate and compare the effectiveness of various information fusion strategies for differentiating mild from moderate-to-severe renal fibrosis in patients with ... read more

Volumetric Analysis of Deep Cerebellar and Thalamic Nuclei in Spastic Cerebral Palsy.

Journal of computer assisted tomography May 25, 2026

OBJECTIVE: Cerebral palsy (CP) encompasses various movement disorders, most commonly spasticity, although other motor phenotypes such as dystonia may occur. Certain structural magnetic resonance imaging (MRI) findings, such as periventricular leukoma... read more

Generative Autoencoders Coupled to Monte Carlo Simulation Allow Efficient Protein Conformation Sampling.

Journal of chemical theory and computation May 25, 2026

Molecular simulations of proteins are well-known to be computationally expensive. Here, we present a new latent-space-based method for modeling protein conformational flexibility at a very affordable computational cost. The method is data-driven and ... read more

Artificial Intelligence Medical Compendium