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

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

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

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

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)...

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease

Clinical and Pathological Heterogeneity of Alzheimer’s Disease and Patterns of Glial Cell Activation Academic Background Alzheimer’s Disease (AD), as the primary cause of dementia in the elderly, has always been a hot topic in research due to its pathological heterogeneity. Previous studies have indicated that the clinical symptoms of AD are divers...

Staged Bilateral MRI-Guided Focused Ultrasound Subthalamotomy for Parkinson Disease

MRI-Guided Staged Bilateral Focused Ultrasound Subthalamotomy for Parkinson’s Disease Background Parkinson’s Disease (PD) is a common neurodegenerative disorder, characterized mainly by motor symptoms such as tremor, rigidity, and bradykinesia. Traditionally, treatments for PD include medication and surgical interventions such as Deep Brain Stimula...