Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 4,261 to 4,270 of 203,842 articles

A machine-learning approach to predict additional treatment after Bacillus Calmette-Guérin induction in non-muscle-invasive bladder cancer.

Scientific reports Jun 2, 2026
Non-muscle invasive bladder cancer (NMIBC) comprises ~ 75% of newly diagnosed bladder cancer, with high-risk NMIBC associated with high rates of recurrence and progression. Nearly 40% of patients experience a lack of efficacy with gold standard Bacil... read more 

DeepRank-Ab: a scoring function for antibody-antigen complexes based on geometric deep learning.

Communications biology Jun 2, 2026
Gaining structural insights into antibody-antigen interactions is essential for understanding immune recognition and therapeutics design. Accurately modeling these complexes remains challenging for both physics-based approaches and AI-based, co-foldi... read more 

Mixed-methods study on GenAI Usage, dependence behaviors, and standardized application paths among Chinese medical students.

NPJ digital medicine Jun 2, 2026
Generative artificial intelligence (GenAI) is reshaping medical education while fostering technological dependence among students. This study employed an explanatory sequential mixed-methods design. In the quantitative phase, an empirical analysis wa... read more 

Deep learning prediction of pathological complete response in breast cancer using Mamba architecture.

NPJ digital medicine Jun 2, 2026
Deep learning is capable of efficiently predicting the therapeutic efficacy of neoadjuvant chemotherapy (NAC) in breast cancer. However, current methods predominantly rely on convolutional neural networks or transformer architectures and are often va... read more 

Development and early feasibility testing of machine-learning algorithms to non-invasively assess hemoglobin levels.

npj biomedical innovations Jun 2, 2026
The HeMonitor study evaluated the feasibility and accuracy of non-invasive hemoglobin (Hb) assessment using image-based techniques and machine learning in patients with hematologic malignancies. A total of 367 patients with hematologic malignancies a... read more 

Chaotic and complex dynamics expose the limits of counterfactual reasoning.

Scientific reports Jun 2, 2026
Counterfactual reasoning, a cornerstone of human cognition and decision-making, is often seen as the "holy grail" of causal learning, with applications ranging from interpreting machine learning models to promoting algorithmic fairness. While counter... read more 

Rapid monitoring of drought and salinity stress responses in wheat via potential Raman-derived biomarkers and traditional biochemical indicators.

Scientific reports Jun 2, 2026
Abiotic stresses such as drought and salinity significantly constrain the productivity of in vitro-grown wheat (Triticum aestivum L.) by disrupting its biochemical and physiological homeostasis. Rapid, non-destructive, and data-driven diagnostic appr... read more 

The Open Materials 2024 (OMat24) inorganic materials dataset and models.

Nature computational science Jun 2, 2026
The discovery and simulation of inorganic materials is core to diverse applications from climate change to semiconductor manufacturing. Artificial intelligence has the potential to dramatically accelerate materials simulation, discovery and design. A... read more 

An explainable machine learning approach to predict fragility fractures and the identification of important features.

Scientific reports Jun 2, 2026
In this study, we developed ML algorithms to predict fragility fractures, considering the occurrence of fractures at different skeletal sites, using the data from the Canadian Multicentre Osteoporosis Study (CaMos) with participants aged 50 years or ... read more 

Missing-data-aware machine learning prediction of in-hospital major adverse cardiovascular events after primary percutaneous coronary intervention for ST-segment elevation myocardial infarction.

Scientific reports Jun 2, 2026
Machine learning (ML) offers opportunities to improve prognostication after ST-segment elevation myocardial infarction (STEMI), but real-world registries frequently contain incomplete data, and inappropriate handling of missingness may degrade perfor... read more 
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