Artificial Intelligence Medical Compendium

Scientific imaging instruments often acquire multiple physically complementary signals within a single measurement. In atomic force microscopy (AFM), high-throughput imaging requires higher scan speeds, however, image quality is fundamentally limited... read more 

OBJECTIVES: To investigate the longitudinal effects of an ambient artificial intelligence (AI) scribe use in primary care on outcomes related to documentation time, note writing patterns, and clinician financial productivity. MATERIALS AND METHODS: W... read more 

Autonomous computing systems are crucial for distributed intelligent electronics, yet conventional architectures continue to face challenges in energy efficiency and system integration. Here, we report a self-powered mechanical intelligence paradigm ... read more 

High-throughput multi-omics technologies generate high-dimensional, heterogeneous and noisy datasets, making robust biomarker discovery and disease modelling challenging. This review critically examines dimensionality reduction and representation str... read more 

OBJECTIVES: Examine the "last mile problem" in artificial intelligence (AI) applications for preventive public health. STUDY DESIGN: Conceptual short communication introducing a five-stage pathway to examine where AI-enabled prevention breaks down. M... read more 

OBJECTIVES: This scoping review examined how artificial intelligence is applied in multidisciplinary and cross-sector public health practice, focusing on public health roles, collaborative implementation, and cross-sector governance and equity risks.... read more 

Time-to-event models are central to aging research, quantifying both whether and when an event occurs. However, guidance on selecting among traditional statistical and machine learning (ML) methods for prediction modeling remains limited, particularl... read more 

Live bacterial vectors combine intrinsic adjuvanticity, mucosal targeting, and programmable antigen delivery within a single engineerable chassis, yet their development has historically relied on empirical attenuation rather than systematic design. W... read more 

High-field MRI offers superior SNR but is constrained by the trade-off between spatial resolution and acquisition time. Existing global deep learning super-resolution (SR) methods often incur computational overhead by ignoring regional image content.... read more 

BACKGROUND: Ischemic heart disease (IHD) is the leading global cause of years of life lost. Although the clinical presentation and progression of IHD differ widely, clinical management is relatively uniform. To improve risk stratification and clinica... read more