AI Medical Compendium

Predicting Bacterial Radiation Resistance Through Identifying Novel Genomic Features.

Environmental microbiology Jun 1, 2026

Radiation resistance in bacteria is a critical trait with implications for biotechnology, medicine and environmental science. Deinococcus species possess unique genomic features that enable their extraordinary survival in extreme environments. Howeve... read more

Predicting Depression Risk in Physically Inactive Older Adults Using Dietary Antioxidants and Machine Learning: A SHAP-Interpretable Analysis of NHANES.

CNS neuroscience & therapeutics Jun 1, 2026

BACKGROUND: Physically inactive older adults represent a high-risk group for depression. However, whether dietary antioxidant intake profiles can help stratify depression risk within this population has not been well established. This study aims to e... read more

Learning-assisted locality optimisation in online suffix tree construction: Formal analysis and empirical validation.

Computational biology and chemistry Jun 1, 2026

Suffix trees underpin many string-processing applications, yet their classical O(n) construction algorithms suffer in practice from the gap between processor and memory speeds: cache misses, not arithmetic operations, dominate wall-clock time. This p... read more

Unveiling the cognitive features of L2 Chinese reading: Machine learning reveals subskill-specific and general eye-movement patterns.

Acta psychologica Jun 1, 2026

Traditional reading assessments rely heavily on offline summative outcomes, obscuring the implicit cognitive dynamics of online processing. To render these latent cognitive dynamics empirically tractable, this study employs a data-driven machine lear... read more

Artificial intelligence empowered coronary artery imaging: A review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 1, 2026

Cardiovascular disease is the leading cause of death worldwide, with coronary artery disease the most prevalent cause. Although artificial intelligence has advanced medical imaging, few reviews focus specifically on AI-powered coronary artery imaging... read more

Artificial intelligence for real-time motion tracking in MRI-guided radiotherapy: A systematic review.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jun 1, 2026

BACKGROUND AND PURPOSE: Intrafraction motion compromises accurate dose delivery in MRI-guided radiotherapy (MRIgRT), motivating the adoption of artificial intelligence (AI). This systematic review aims to evaluate the performance of AI-driven motion ... read more

Evolution of PM2.5 chemical composition during summer new particle formation in a coastal city in the Yangtze River Delta: insights from pollution episodes, machine learning, and air mass origins.

Environmental research Jun 1, 2026

To investigate the influence of O3 on new particle formation (NPF) events and associated changes in PM2.5 chemical composition, an observation campaign was conducted in suburban Wuzhen, Jiaxing from August to September 2024. A total of 13 NPF events ... read more

Synergistic dual-strategy incorporating hollow-structuring and deposition of MoSχ conductive layer for enhancing photocatalytic activity of ZnO.

Environmental research Jun 1, 2026

Despite methods for improving photo-activity have been proposed over years, the synergism from coupling them remains mystery. Therefore, current study unveils this by incorporating both hollow-structuring and deposition of conductive layer in one-sin... read more

Advances in biosensors for monitoring immune responses and allograft rejection in organ transplantation.

Transplant immunology Jun 1, 2026

Organ transplantation remains a gold-standard intervention for numerous end-stage organ failure diseases. However, allograft rejection is still a barrier to long-term graft survival. Conventional allograft monitoring approaches, including tissue biop... read more

Machine learning assessment of pathologic response in lung cancer resections after neoadjuvant therapy - IASLC MPR Project.

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer Jun 1, 2026

INTRODUCTION: Machine learning algorithms may improve efficiency and accuracy of pathologic response (PR) assessment in surgically resected lung cancers following neoadjuvant therapy. The aim of this study was to develop digital models for quantifyin... read more

Artificial Intelligence Medical Compendium