Artificial Intelligence Medical Compendium

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

Showing 261 to 270 of 199,772 articles

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 

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 

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 

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 

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 

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 

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Scientific reports Jun 2, 2026
Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening coverage remains low at 7-25.3%, far below the WHO target of 70%. Increasing women's knowledge about ... read more 

Integrating generalized linear mixed models and XGBoost for safety performance function development on urban arterials.

Scientific reports Jun 2, 2026
Urban arterial corridors present elevated crash risk due to high traffic volumes, complex geometries, and interactions among diverse road users. This study develops Safety Performance Functions (SPFs) for urban arterial segments in Southeast Michigan... read more 

Fault tolerance in para-line network topologies: theory and applications in smart systems.

Scientific reports Jun 2, 2026
This study explores the fault-tolerant metric dimension (FTMD) of the para-line network, which is derived from the n-sunlet network, a significant category of networks created by subdividing and transforming cycle-based networks to simulate greater s... read more 

Large-scale multimodal pre-trained model driven ceramic design knowledge graph construction and cross-domain innovative design reasoning mechanism.

Scientific reports Jun 2, 2026
This paper presents a novel framework integrating large-scale multimodal pre-trained models with knowledge graph technologies to advance ceramic design innovation. We propose a comprehensive methodology for constructing domain-specific knowledge grap... read more 
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