The aim of this study was to establish the optimal prediction model by comparing the prediction effect of 6 kinds of prediction models containing biochemical indexes on the risk of osteoporosis in middle-aged and elderly women in Tibet. This study ad...
In our study, we aim to predict the antibody serostatus of patients with suspected autoimmune encephalitis (AE) using machine learning based on pre-contrast T2-weighted MR images acquired at symptom onset. A confirmation of seropositivity is of great...
Pancreatic cancer (PC) is a fatal disease with an extremely low 5-year survival rate, mainly because of its poor detection rate in early stages. Given emerging evidence of the relationship between microbiota composition and diseases, this study aims ...
Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its a...
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...
BACKGROUND: Chronic pain, affecting more than 20% of the global population, has an enormous pernicious impact on individuals as well as economic ramifications at both the health and social levels. Accordingly, tools that enhance pain assessment can c...
BACKGROUND: In low- and middle-income countries, cervical cancer remains a leading cause of death and morbidity for women. Early detection and treatment of precancerous lesions are critical in cervical cancer prevention, and colposcopy is a primary d...
BACKGROUND: Vancomycin is commonly dosed using standard weight-based methods before dose adjustments are made through therapeutic drug monitoring (TDM). However, variability in initial dosing can lead to suboptimal therapeutic outcomes. A predictive ...
BACKGROUND: As large language model (LLM)-based chatbots such as ChatGPT (OpenAI) grow in popularity, it is essential to understand their role in delivering online health information compared to other resources. These chatbots often generate inaccura...
BACKGROUND: Alzheimer disease and related dementias (ADRD) exhibit prominent heterogeneity. Identifying clinically meaningful ADRD subtypes is essential for tailoring treatments to specific patient phenotypes.