Research Insights in American hhm – American Healthcare Magazine

Large language models and artificial intelligence for generating, simplifying, and enhancing outpatient clinic letters: A systematic review

Outpatient clinic letters are a cornerstone of clinical communication but frequently exceed recommended reading levels limiting patient comprehension and engagement Large Language Models LLMs

A systematic review of prolonged posture monitoring with accelerometer-based wearable sensors

Prolonged sitting and standing are associated with health risks Unlike generic sedentary behaviour monitoring based on energy expenditure prolonged posture monitoring requires posturespecific detection

A segmentation-guided CNN–Vision transformer feature fusion framework for multi-class breast ultrasound image classification

Breast ultrasound BU imaging is widely used for detecting breast abnormalities because it is costeffective noninvasive and suitable for dense breast tissue However multiclass classification of BU images

A machine learning model for predicting ischemic and bleeding risk after percutaneous coronary intervention: Development and external validation

This study aimed to develop and externally validate a machine learningbased risk prediction model of ischemia and bleeding events in patients receiving percutaneous coronary intervention

A context-aware temporal modeling through unified multi-scale temporal encoding and hierarchical sequence learning for single-channel EEG sleep staging

Automatic sleep staging is a critical task in healthcare due to the global prevalence of sleep disorders This study focuses on singlechannel electroencephalography EEG a practical and widely available signal

Functional alterations of neutrophils from β-thalassemia patients exposed to Pythium insidiosum: An ex vivo study

Patients with thalassemia are highly susceptible to Pythium insidiosum the causative agent of human pythiosis a severe and often lifethreatening disease in tropical regions This vulnerability has been associated

Graph theory-based machine learning for automated fibromyalgia diagnosis using fMRI during an emotional task

Fibromyalgia FM is a multifaceted chronic pain disorder presenting with pain throughout the musculoskeletal system alongside chronic fatiguesleep disturbances and cognitive impairments Current diagnostic criteria primarily rely on symptom questionnaires with no specific laboratory markers or definitive tests making diagnosis subjective and often de...

A medically grounded LLM agent–based tool to detect patient safety events in medical records

Large language models LLMs have shown incredible promise in medicine While LLMs may be particularly useful in areas requiring extensive review of clinical records their use remains limited

Methods for cost-efficient, whole genome sequencing surveillance for enhanced detection of outbreaks in a hospital setting

Outbreaks of healthcareassociated infections HAI result in substantial patient morbidity and mortality mitigation efforts by infection prevention teams have the potential to curb outbreaks and prevent transmission

Multi-view attention-based deep learning for benign–malignant classification of pulmonary nodules

Accurate classification of pulmonary nodules is essential for early lung cancer diagnosis yet the limited spatial information provided by a single computed tomography slice may hinder the characterization