Latest AI and machine learning research in endocrinology for healthcare professionals.
Ask a pretrained biomedical language model whether "cortisol 28 ug/dL" and "stock-market volatility" are related, and it returns a cosine similarity of 0.83 on a scale where 1.0 means identical. The two share no mechanism. This is not a corner case: every off-the-shelf biomedical encoder we tested (BioBERT, PubMedBERT, BioM-ELECTRA) scores unrelated cross-domain pairs between 0.76 and 0.92 when th...
Background: It is an everyday observation that people of the same chronological age differ with respect to their physical and mental capacity. However, assessing these differences in biological age remains challenging. Methods: Here, we aggregate 89 age-associated variables from the Berlin Aging Study II (BASE-II, n=1,631) to generate MultiAge, a new marker of biological age that summarizes inform...
Background: Endoscopic endonasal transsphenoidal surgery (EETS) requires navigation around neurocritical anatomy. Today, artificial intelligence clini...
Background Endoscopic pituitary surgery involves navigating high-stakes anatomy where complications, such as carotid artery injury, cause devastating ...
Artificial intelligence (AI) decision support systems for surgery hold promise but face barriers to adoption, particularly around the interpretability...
Continuous glucose monitoring (CGM) enables personalized metabolic health support, but forecasting glucose in free-living settings remains challenging...
Objective: Despite the complex and non-linear progression of diabetes, its shared pathways with atherosclerotic cardiovascular disease (ASCVD) are con...
Objective To develop clinically operational, population-representative risk-score models for detecting metabolic syndrome (MetS) in U.S. adults by inc...
Background/Aims: Neovascular glaucoma (NVG) is an aggressive secondary glaucoma with limited longitudinal data. This study reports the aetiologies, tr...
Osteoporosis is often called a silent disease because it progresses without symptoms until a fracture occurs, posing a serious, yet frequently overloo...
Importance: Prenatal exposure to gestational diabetes mellitus (GDM) has been associated with adverse metabolic, neurodevelopmental, and psychiatric o...
Insulin therapy for type 1 diabetes requires continual dose adjustment to meals, activity, stress, illness, and changing insulin sensitivity, creating...
This study developed a new Cellular Omics-Structural Integration (COSI) technology platform to address the limitation of traditional technologies in s...
Objectives: Diabetes affects over 500 million people globally and glycemia is inadequately managed. Metformin is the most frequently prescribed initia...
Diabetes is a chronic metabolic disease that can lead to serious health problems if not diagnosed and managed early. Big Data Analytics (BDA) and mach...
Biomedical image segmentation is a critical task in medical diagnosis and treatment planning, enabling precise delineation of anatomical structures an...
Diabetes is a global health burden, and early detection is critical for timely intervention. This study explores a non-invasive, data-driven framework...
Background: Heart failure (HF) is a major contributor to inpatient hospital utilization, with persistently high 30-day readmission rates. Existing pre...
Light microscopy imaging with histological stains is central to disease diagnosis and research. It is enhanced with immunostaining to reveal cellular ...
Metabolomic aging clocks estimate biological age by modeling metabolite concentrations, thereby capturing aging signals from healthspan and adverse ou...