Artificial Intelligence Medical Compendium

OBJECTIVES: To evaluate the clinical utility of photon counting computed tomography (PCCT)-derived quantitative parameters for assessing interstitial lung disease (ILD) burden in patients with inflammatory idiopathic myopathy (IIM), comparing standar... read more 

Artificial intelligence (AI) is increasingly being integrated into clinical radiology workflows and has the potential to make a significant contribution to patient care in the future. Although there is currently insufficient evidence to enable a defi... read more 

Reliable assessment of mesenchymal stromal cell (MSC) viability and stem cell-associated properties is essential for ensuring the consistency, safety, and therapeutic potential of MSC cultures before clinical use. However, incomplete understanding of... read more 

Dengue fever is a viral infection transmitted to humans through the bites of infected mosquitoes. Modeling dengue transmission is crucial for control, given its risk to half the world's population. This paper develops a host-to-host transmission mode... read more 

Large language models (LLMs) have demonstrated human-level performance in literature review screening phases and have been evaluated in systematic-review workflows. However, LLM performance in scoping reviews, which are broader and more heterogeneous... read more 

Obesity, hyperglycemia, and aging are major risk factors for dementia-related disorders, particularly Alzheimer's disease. We develop a time-fractional reaction-diffusion mathematical framework integrating nine interacting biological compartments gov... read more 

Surgical robots in clinical use operate under continuous human control, yet research systems now perform surgical tasks on their own. Patient willingness may limit adoption, and to our knowledge no study has measured willingness across defined levels... read more 

PURPOSE OF REVIEW: Cardiac implantable electronic device (CIED) infection remains one of the most serious complications of device therapy, causing significant morbidity, mortality, healthcare utilization, and costs. Despite advances in device technol... read more 

OBJECTIVES: This study implements and evaluates a deep learning approach to enhance FA, MD, AD, and RD maps derived from 16-direction DTI to approximate corresponding maps derived from 32-direction DTI, with the aim of reducing acquisition time while... read more 

Estimating heterogeneous treatment effects in survival settings is complicated by right censoring as well as the time-varying nature of the estimand. While the conditional average treatment effect (CATE) provides a natural target, most existing appro... read more