Diabetes

A blueprint for mutation-defined hallmark vulnerabilities across human cancers

Hallmark gene mutations shape cancer cell vulnerabilities and inform drug discovery1–3. A systematic map of hallmark gene mutation-defined cancer dependencies and therapeutic responses is essential to uncover novel targets and refine therapeutic strategies. Here, we present the first pan-cancer blueprint of hallmark vulnerabilities, systematically linking hallmark gene mutation markers to cancer c...

Dual-Field Microvascular Segmentation: Hemodynamically-Consistent Attention Learning for Retinal Vasculature Mapping

Accurate retinal Microvascular segmentation demands a balanced combination of anatomical fidelity and hemodynamic relevance. However, existing methods fall short in preserving critical structures such as capillary junctions and bifurcations, thus limiting clinical applications and causing fragmentation. To address these limitations, we propose DFMS-Net, a novel dualfield segmentation framework tha...

Disentangling covariate effects on single cell-resolved epigenomes with DeepDive

Understanding the effects of individual biological factors from single cell-resolved epigenomic data is hindered by multicollinearity, particularly in...

Integrating Genomics into Multimodal EHR Foundation Models

This paper introduces an innovative Electronic Health Record (EHR) foundation model that integrates Polygenic Risk Scores (PRS) as a foundational data...

Deep Learning Enables Automated Segmentation and Quantification of Ultrastructure from Transmission Electron Microscopy Images

The widths of kidney glomerular basement membrane (GBM) and podocyte foot processes (FP) are essential ultrastructural markers for assessing kidney fu...

Decoding Diabetes: Harnessing AI to Accurately Predict Real-Time and Future Blood Glucose Levels for Diabetes Management Using Diet, Exercise, Insulin Intake, and Heart Rate Variability

Continuous glucose monitoring (CGM) systems play a crucial role in diabetes care. Yet, they focus solely on blood glucose levels (BGL), neglect diet, ...

Identification of SASP-associated biomarkers and regulatory mechanisms in diabetic foot ulcers based on transcriptomics and experimental validation

Diabetic foot ulcers (DFU) constitute a major complication arising from diabetes mellitus. Emerging research findings have underscored the pivotal con...

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...

Integration of artificial intelligence and high-content screening enabled identification of drugs for long-term treatment of cerebral cavernous malformation disease

Adults and children with cerebral cavernous malformations (CCMs) are at risk of experiencing lifelong complications such as hemorrhagic strokes, neuro...

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...

Retinal vascularization rate predicts retinopathy of prematurity and remains unaffected by low-dose bevacizumab treatment

To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor...

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...

EpiPathAI: Using Large Language Models to Explore Mechanisms of Life Course Exposure-Outcome Associations

Large language models (LLMs) enhanced with Graph Retrieval-Augmented Generation (GRAG) are promising for life-course epidemiology, which typically dep...

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...

An Efficient and Interpretable Foundation Model for Retinal Image Analysis in Disease Diagnosis

Artificial intelligence (AI) foundation models for colour fundus photography (CFP) have been extensively studied and demonstrated great potential for ...

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 ...

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...