AI Medical Compendium

Precursor flat urothelial lesions: Molecular landscape, pathogenesis, and biological insights.

Pathology, research and practice May 11, 2026

Flat urothelial lesions represent a diagnostically challenging and clinically significant spectrum in bladder pathology. Distinguishing urothelial carcinoma in situ (CIS) from precursor lesions such as dysplasia remains problematic due to overlapping... read more

Foundation for Artificial Intelligence-Driven Democratization of Healthcare Access.

Learning health systems May 11, 2026

INTRODUCTION: Healthcare systems worldwide face unprecedented challenges, including escalating costs, workforce shortages, and access disparities, which threaten their sustainability. The WHO projects an 18 million healthcare worker deficit by 2030, ... read more

Associations of Red Blood Cell Distribution Width-Derived Indicators and Their Longitudinal Dynamic Trajectories With Mortality Risk in Critically Ill Patients With Pulmonary Hypertension.

Pulmonary circulation May 11, 2026

Red blood cell distribution width (RDW)-derived indicators have increasingly been recognized as biomarkers reflecting systemic inflammation and hematological disorders. However, the prognostic value of these indicators in critically ill patients with... read more

Diagnostic Performance of a Large Language Model (ChatGPT-4o) in Chronic Rhinosinusitis CT Scan Interpretation.

Laryngoscope investigative otolaryngology May 11, 2026

BACKGROUND: Large language models (LLMs), such as ChatGPT, are increasingly utilized by physicians for clinical decision support due to their ease of use and versatility. However, their performance in diagnostic imaging remains largely untested. This... read more

Application of machine-learning algorithms to identify the key determinants of risk for HIV, hepatitis C and hepatitis B in primary care settings.

BMC infectious diseases May 11, 2026

BACKGROUND: Testing for Blood-Borne-Viruses (BBVs) such as the human immunodeficiency virus (HIV), hepatitis C virus (HCV) and hepatitis B virus (HBV) is generally focused on specialist settings. However, people with undiagnosed infections are also p... read more

Research on the efficacy of hybrid deep learning models for image-based classification of common oral conditions.

BMC oral health May 11, 2026

OBJECTIVE: To compare tuned end-to-end and hybrid deep learning strategies for image-based classification of common oral conditions under small and imbalanced data conditions, and to determine whether the same pattern persists in a clinically focused... read more

Are AI chatbots ready for chikungunya public education? Evidence on validity, reliability, and readability.

BMC public health May 11, 2026

BACKGROUND: Chikungunya continues to expand geographically, driving demand for trustworthy, easy-to-read public guidance. Conversational AI systems are increasingly used for health information, yet their medical validity, reliability, and readability... read more

Explainable retinal deep learning for cardiovascular risk stratification: a multiple modality analysis framework with vascular-centric interpretability and robustness.

BMC medical informatics and decision making May 11, 2026

Early non-invasive prediction of cardiovascular risk is an essential prerequisite for preventive medicine, especially in resource-limited settings. Retinal imaging provides unique insights into systemic vascular health; however, most existing deep le... read more

Alterations in resting-state neural networks in subacute non-fluent aphasia after stroke: a fNIRS study.

BMC neurology May 11, 2026

BACKGROUND: Post-stroke aphasia is a prevalent and often disabling language impairment. Despite its high incidence, the neuropathological mechanisms underlying post-stroke aphasia and the neural substrates of functional recovery remain poorly underst... read more

Development and internal validation of an explainable machine-learning model to predict 3-year overall survival rate after radical cystectomy.

BMC cancer May 11, 2026

BACKGROUND: This study aimed to develop and internally validate an explainable machine-learning model using routinely available clinicopathologic and laboratory variables for predicting 3-year overall survival (OS) after radical cystectomy. METHODS: ... read more

Artificial Intelligence Medical Compendium