AI Medical Compendium

EXPRESS: Artificial Intelligence in Diabetes Care: Toward Precision Diagnosis and Personalized Management.

Journal of investigative medicine : the official publication of the American Federation for Clinical Research May 13, 2026

AimsDiabetes mellitus is a global health challenge requiring innovative solutions for early diagnosis, personalized treatment, and ongoing management. This review aims to examine the impact of artificial intelligence (AI) on diabetes care, focusing o... read more

Adrenal gland dysfunction in males with cluster headache.

The journal of headache and pain May 13, 2026

BACKGROUND: Cluster headache is associated with compensated hypogonadism in males, suggesting impaired testicular steroidogenesis. It is unknown if adrenal steroidogenesis is dysregulated and how this is linked to cluster headache pathophysiology. We... read more

Impaired glymphatic function and advanced brain age gap in chronic migraine: a multimodal MRI study.

The journal of headache and pain May 13, 2026

OBJECTIVES: This study investigated whether the coupling between cortical blood-oxygen-level-dependent (BOLD) signals and cerebrospinal fluid (CSF) flow, a physiologically motivated but indirect proxy related to glymphatic-associated dynamics, modera... read more

An automated workflow for fungal cell counting, cell size and data analysis: enhancing throughput and accuracy with the cell analysis and counting tool using ilastik software (caactus).

BMC microbiology May 13, 2026

BACKGROUND: The development of filamentous fungal cells from spore to mature mycelium is influenced by a myriad of environmental conditions. Traditional methods for quantifying various fungal cell morphologies in liquid media via microscopy are labor... read more

Early prediction of intraoperative hypotension: development and validation of the HypoBridCast hybrid deep learning model.

BMC anesthesiology May 13, 2026

BACKGROUND: Intraoperative hypotension (IOH) is a frequent and clinically important complication associated with adverse postoperative outcomes. Early prediction may facilitate timely intervention, although existing models have limitations in integra... read more

Parents' knowledge, attitudes, and concerns regarding the use of artificial intelligence in pediatric medicine: a cross-sectional study.

BMC pediatrics May 13, 2026

BACKGROUND: Artificial intelligence (AI) is increasingly applied in pediatric healthcare, with the potential to improve diagnostic and treatment accuracy and efficiency. However, parental acceptance and trust are critical for successful implementatio... read more

Non-traditional metabolic indices predict incident circadian syndrome in middle-aged and older Chinese adults: a nationwide prospective cohort study and machine learning analysis.

Lipids in health and disease May 13, 2026

BACKGROUND: Circadian syndrome (CircS) augments the conventional metabolic syndrome construct by adding disturbed sleep and depressive features. Whether composite metabolic indices that combine insulin-resistance, atherogenic-lipid, and inflammatory ... read more

Artificial intelligence models in cerebral infarction: performance and applications in diagnosis, classification, grading, treatment, and disease course prediction-a systematic review.

BMC medical informatics and decision making May 13, 2026

Artificial intelligence (AI) holds significant promise for transforming cerebral infarction care, yet its real-world performance across the entire disease management continuum remains inadequately synthesized, with heterogeneous evidence and unclear ... read more

Development and internal validation of a machine learning-based model for predicting postoperative complications after primary liver cancer resection.

BMC surgery May 13, 2026

OBJECTIVE: To identify risk factors for postoperative major complications after resection of primary liver cancer and to develop machine learning-based risk prediction models. We compared the predictive performance of multiple machine learning algori... read more

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.