AI Medical Compendium

CAHA-Net: A novel MR image classification model based on DenseNet incorporating coordinate attention and hybrid augmentation.

Scientific reports May 28, 2026

Traditional diagnostic approaches are time-consuming and labor-intensive, and the field currently lacks a comprehensive evaluation of mainstream models that addresses their complementary strengths. Computer-aided diagnosis methods can significantly i... read more

Radiation dose has no significant impact on CT-based bone mineral density measurements in a large-animal model.

Scientific reports May 28, 2026

Bone mineral density (BMD) is a biomarker for frailty, and CT-derived radiodensity can be extracted fully automatically as a surrogate. Because these measurements might be affected by image noise, which varies substantially in the clinical routine, t... read more

Guideline for secondary use of health records within Norwegian and EU regulatory frameworks.

NPJ digital medicine May 28, 2026

Secondary use of health records is vital for research, quality improvement, innovation, but it must comply with complex legal, ethical, and security requirements. In Norway and the European Economic Area (EEA), this involves navigating national healt... read more

Cross-material catalyst discovery via deep learning.

Nature materials May 28, 2026

The discovery of catalysts is typically confined within individual material classes, limiting insight from across material types. Here we demonstrate a machine learning approach that bridges catalyst families by identifying co-descriptors derived fro... read more

FLOWR: flow matching for structure-aware de novo, interaction- and fragment-based ligand generation.

Nature computational science May 28, 2026

Here we introduce FLOWR, a structure-based framework for the generation and optimization of three-dimensional ligands. FLOWR integrates continuous and categorical flow matching with equivariant optimal transport, enhanced by an efficient protein pock... read more

Uncertainty-Aware Super-Resolution for Mammography Phantoms using a Dropout-Enabled SwinIR.

Journal of imaging informatics in medicine May 28, 2026

This study was aimed at presenting a framework integrating uncertainty quantification into the SwinIR super-resolution model for mammography, addressing the "black box" limitation that hinders clinical trust. Monte Carlo (MC) Dropout was incorporated... read more

VMAM-NET: A Model Agnostic Meta-Learning Network for Rare De Novo Glioblastoma Diagnosis.

Journal of imaging informatics in medicine May 28, 2026

The diagnosis of grade IV brain tumors, such as de novo glioblastoma, has recently attracted a lot of scientific interest in neuroimaging and deep learning. Glioblastoma, a very rare and highly aggressive brain tumor, poses considerable diagnostic ch... read more

OpenRad: a curated repository of open-access AI models for radiology.

European radiology May 28, 2026

OBJECTIVES: To create and evaluate OpenRad ( https://konstvr.github.io/OpenRad/index.html ), a curated, standardized repository that aggregates open-access radiology artificial intelligence (AI) models enriched with metadata from the corresponding co... read more

Artificial intelligence in cancer immunotherapy: current trends in predicting response and personalizing treatment.

Journal of the Egyptian National Cancer Institute May 28, 2026

Artificial intelligence (AI) can transform cancer immunotherapy by enabling more accurate prediction of treatment responses, the discovery of specific biomarkers, and the development of personalised treatment plans. Traditional single-marker biomarke... read more

Artificial intelligence and transforming cancer care.

Discover oncology May 28, 2026

Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized approaches from diagnosis to treatment. This review explores the transformative role of AI across the c... read more

Artificial Intelligence Medical Compendium