Endocrinology

MetaPaCS: A Novel Meta-Learning Framework for Pancreatic Cancer Subtype Identification

As the third leading cause of cancer related deaths in the United States, pancreatic cancer (PaC) is a highly heterogenous malignancy that can be divided into a multitude of potential subtypes, with the main 4 consisting of aberrantly differentiated endocrine exocrine (ADEX), immunogenic, progenitor, and squamous. Each PaC subtype is characterized by their unique molecular pathways and therapeutic...

Phenotypic Screening Coupled with AI-Driven Target Deconvolution Identifies α-Terthienyl as a Dual DPP-IV/HSD17β13 Modulator with Efficacy in a Mouse Model of MASLD

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent condition characterized by fat build-up in the liver and ranges from benign steatosis to progression to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis and end-stage liver disease including hepatocellular carcinoma, representing a significant cause of chronic liver disease globally.1...

Machine Learning-Augmented Analysis of Nano-electrochemical Sensor Data for Predictive and Quantitative Assays of Complex Biological Samples

Analytical chemistry provides the content of nearly every scientific, technical and business decision relating to what atoms, molecules and devices ar...

Identification of genomic features that uniquely impact estrogen receptor alpha binding and its effects on gene expression in endometrial cancer

Estrogen receptor alpha (ER) is an established oncogenic transcription factor in breast and endometrial cancer; however, more is known about the mecha...

GLUCOSE: A Distributional Reinforcement Learning Model for Optimal Glucose Control After Cardiac Surgery

This study introduces Glucose Level Understanding and Control Optimized for Safety and Efficacy (GLUCOSE), a distributional offline reinforcement lear...

Significant Reduction in Manual Annotation Costs in Ultrasound Medical Image Database Construction Through Step by Step Artificial Intelligence Pre-annotation

This study investigates the feasibility of reducing manual image annotation costs in medical image database construction by utilizing a step by step a...

Assessing Inflammatory Protein Biomarkers in COPD Subjects with and without Alpha-1 Antitrypsin Deficiency

Individuals homozygous for the Alpha-1 Antitrypsin (AAT) Z allele (Pi*ZZ) exhibit heterogeneity in COPD risk. COPD occurrence in non-smokers with AAT ...

Predicting Dementia in People with Parkinson’s Disease

Parkinson’s disease (PD) exhibits a variety of symptoms, with approximately 25% of patients experiencing mild cognitive impairment and 45% developing ...

Impact of Mydriasis on Image Gradability and Automated Diabetic Retinopathy Screening with a Handheld Camera in Real-World Settings

Diabetic retinopathy (DR) screening in low- and middle-income countries (LMICs) faces challenges due to limited access to specialized care. Portable r...

AI-Powered Exploration of IGF2BP3 as a Prognostic Biomarker in Chronic Myeloid Leukemia Progression and Disease Stratification

Chronic Myeloid Leukemia (CML) progresses through chronic, accelerated, and blast crisis phases, making disease stratification and therapeutic respons...

Trust in large language model-based solutions in healthcare among people with and without diabetes: a cross-sectional survey from the Health in Central Denmark cohort

Large language models have gained significant public awareness since ChatGPT’s release in 2022. This study describes the perception of chatbot-assiste...

Development and validation of a multivariable Prediction Model for Pre-diabetes and Diabetes using Easily Obtainable Clinical Data

In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. Hemoglobin A1c is the most common diagnostic test ...

Enhancing Diagnostic Precision in Thyroid Nodule Classification: A Deep Learning Approach to Automated Ultrasound Image Analysis

Escalating thyroid nodule prevalence necessitates precise ultrasonographic diagnosis, which is constrained by operator-dependent variability. Convolut...

Machine Learning-Driven Glycoproteomic Profiling Identifies Novel Diabetes-Associated Glycosylation Biomarkers

Glycosylation plays a critical role in protein function and disease progression, including diabetes mellitus. This study performed a comprehensive gly...

Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood

Type 1 Diabetes (T1D) is a T-cell mediated disease with a strong immunogenetic HLA dependence. HLA allelic influence on the T cell receptor (TCR) repe...

MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e., endophenotypes) that bri...

Plasma Proteomics and Diabetes Duration Predict Aneurysm Incidence and Rupture Using Machine Learning

Early identification of individuals at high risk for aneurysms, particularly ruptured aneurysms, is critical for timely intervention. However, existin...

Evaluating prediction of short-term tolerability of five type 2 diabetes drug classes using routine clinical features: UK population-based study

A precision medicine approach in type 2 diabetes (T2D) needs to consider potential treatment risks alongside established benefits for glycaemic and ca...

Unbiased multi-omics network-based data integration allows clinically relevant outcome-predicting clustering of individuals with heart failure

Heart failure is a multifaceted clinical syndrome, in which the heart fails to supply adequate blood to meet the body’s oxygen and nutrients needs. Ev...

Predicting Depression in Canadians with or at Risk of Diabetes: A Cross-Sectional Machine Learning Analysis

Depression often goes unrecognized in individuals at risk or living with diabetes, presenting considerable challenges for primary care clinicians. Alt...