Latest AI and machine learning research in endocrinology for healthcare professionals.
BACKGROUND: Approximately 40% of patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-), advanced breast cancer (ABC) have PIK3CA alterations, which contributes to endocrine therapy resistance. Alpelisib, an α-selective phosphatidylinositol 3-kinase inhibitor and degrader, given in combination with fulvestrant, is approved for the treatment of PIK3...
Diabetic Retinopathy (DR) is a leading cause of permanent blindness due to the difficulty of early screening. In this context, deep-learning-based automatic DR grading has the potential to significantly improve the diagnostic efficiency of ophthalmologists. However, accurate DR grading remains challenging due to intra-class variations and small lesions. To address this problem, a Lesion Learning N...
Over a century since Louis Camille Maillard first described the reaction that bears his name, advanced glycation end products (AGEs) resulting from th...
Promoting brain health is vital for well-being and reducing healthcare burdens. Brain health as measured with the Brain Age Gap (BAG) - the difference...
A major challenge in deciphering the complex genetic landscape of polycystic ovary syndrome (PCOS) lies in the limited understanding of how susceptibi...
The aim of this study is to develop an artificial intelligence (AI)-driven pipeline for forecasting blood glucose levels to mitigate risks associated ...
We developed an automatic self-enhancement-based perfusion mapping (SEPM) method to relatively map the microvascular perfusion level in contrast-enhan...
AIMS: To establish a model to predict cardiovascular risk and identify treatment response for patients with type 2 diabetes. METHODS: Data from 11677 ...
Thyroid nodule ultrasound (US) images and their features are of great importance in thyroid nodule diagnosis, and can be helpful for radiologists' cli...
OBJECTIVES: This study aimed to identify high-risk factors for type 2 diabetes and develop a machine learning (ML)-based diabetes prediction model usi...
OBJECTIVES: To predict siesta behavior using machine learning models trained on self-reported and objective data-temperature (T), activity (A), positi...
BACKGROUND: The human microbiome profoundly influences the host plasma metabolome and health, but most studies have focused on the gut microbiome in i...
Rapid and accurate detection of pathogenic bacteria remains essential for infection control and timely treatment. Here, we report a graphdiyne (GDY)-b...
Breast cancer (BRCA) heterogeneity necessitates robust prognostic biomarkers. Programmed cell death (PCD) serves a key role in tumor progression and t...
Breast arterial calcifications (BAC) are associated with increased cardiovascular risk and have been correlated with other methods of cardiovascular r...
Obesity has become alarming globally, with mounting health emergencies related to a number of chronic conditions like cardiovascular disease, diabetes...
INTRODUCTION: Artificial intelligence (AI) chatbots are increasingly used in medicine, but their reliability in scenarios with multiple management opt...
BACKGROUND: Preserved ratio impaired spirometry (PRISm), defined by reduced FEV1 with preserved FEV1/FVC ratio, has been linked to cardiometabolic dis...
BACKGROUND: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication that can pose numerous adverse health effects on both mothers an...
BACKGROUND: Albuminuria is a key diagnostic and prognostic biomarker of chronic kidney disease (CKD), associated with adverse cardiovascular and renal...