Strokeclassifier: Ischemic Stroke Etiology Classification by Ensemble Consensus Modeling Using Electronic Health Records

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health, Neurology,
stroke   machine learning   artificial intelligence   etiology classification   health records   diagnostic accuracy   secondary prevention  

StrokeClassifier: An AI Tool for Etiological Classification of Ischemic Stroke Based on Electronic Health Records Project Background and Motivation Identifying the etiology of strokes, particularly acute ischemic stroke (AIS), is crucial for secondary prevention, but it is often very challenging. In the United States, there are nearly 676,000 new c...

Self-Supervised Learning of Accelerometer Data Provides New Insights for Sleep and Its Association with Mortality

Self-Supervised Learning of Accelerometer Data Provides New Insights for Sleep and Its Association with Mortality

Information Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Life Sciences, Biophysics,
self-supervised learning   accelerometer   sleep   mortality   deep learning   sleep stage classification   multicenter cohort study  

Insights into the Association Between Sleep and Mortality Revealed by Self-supervised Learning of Wrist-worn Accelerometer Data In modern society, sleep is an essential basic activity for life, and its importance is self-evident. Accurately measuring and classifying sleep/wake states and different sleep stages is crucial for diagnosing sleep disord...

Development and Validation of Machine Learning Algorithms Based on Electrocardiograms for Cardiovascular Diagnoses at the Population Level

Information Science, Artificial Intelligence, Medicine, Cardiovascular System, Life Sciences, Biophysics,
Artificial Intelligence   Electrocardiogram   Cardiovascular Diseases   Deep Learning   Extreme Gradient Boosting  

Development and Validation of Large-Scale Machine Learning Algorithms for Cardiovascular Diagnosis Based on Electrocardiograms Introduction Cardiovascular diseases (CV) have long been a major source of global disease burden. Early diagnosis and intervention are crucial for reducing complications, healthcare utilization, and associated costs. Tradit...

Impact of a Deep Learning Sepsis Prediction Model on Quality of Care and Survival

Information Science, Artificial Intelligence, Medicine, Nursing, Emergency Medicine,
deep learning   sepsis   prediction model   quality of care   survival rate   in-hospital mortality   causal impact analysis  

Impact of Deep Learning Sepsis Prediction Model on Nursing Quality and Patient Survival Research Background Sepsis is a systemic inflammatory response caused by infection, affecting approximately 48 million people globally each year, with around 11 million deaths. Due to the heterogeneity of sepsis, early identification often faces significant chal...

Large Language Models to Identify Social Determinants of Health in Electronic Health Records

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health, Humanities and Others,
large language models   social determinants of health   electronic health records   natural language processing   model optimization   synthetic data generation  

Using Large Language Models to Identify Social Determinants of Health from Electronic Health Records Background and Research Motivation Social Determinants of Health (SDOH) have a significant impact on patient health outcomes. However, these factors are often incompletely recorded or missing in the structured data of Electronic Health Records (EHR)...

Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models

Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models

Information Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Oncology,
cascaded diffusion models   RNA sequencing   synthetic images   tumors   machine learning   data scarcity   multimodal data  

Generation of Synthetic Whole-Slide Images of Tumors from RNA Sequencing Data via Cascaded Diffusion Models A recent study published in Nature Biomedical Engineering, titled “Generation of Synthetic Whole-Slide Image Tiles of Tumours from RNA-Sequencing Data via Cascaded Diffusion Models,” has garnered significant attention. This research, conducte...