To analyze radiomics features of cardiac adipose tissue in individuals with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD), integrating relevant clinical indicators, and employing machine learning techniques to construct a preci...
Stroke is a significant health concern in China. Differences in stroke risk between rural and urban areas have been highlighted in prior research. However, there is a scarcity of studies on urban-rural differences in predicting stroke. This study aim...
This research aims to design and validate a machine learning model to predict the probability of urinary tract infections within 90 days post-urostomy in bladder cancer patients. Clinical and follow-up information from 317 patients who had urostomy p...
This study was conducted to develop and validate a novel deep reinforcement learning (DRL) algorithm incorporating the segment anything model (SAM) to enhance the accuracy of automatic contouring organs at risk during radiotherapy for cervical cancer...
The growing acknowledgment of population wellbeing as a key indicator of societal prosperity has propelled governments worldwide to devise policies aimed at improving their citizens' overall wellbeing. In New Zealand, the General Social Survey provid...
BACKGROUND: Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss complaints to dementia diagnosis remains limited.
BACKGROUND: We retrospectively evaluated the quality of deep learning (DL) reconstructions of on-scanner accelerated intraoperative MRI (iMRI) during respective brain tumor surgery.
Parkinson's Disease (PD) is a growing burden with varied clinical manifestations and responses to Subthalamic Nucleus Deep Brain Stimulation (STN-DBS). At present, there is no effective and simple machine learning model based on comprehensive clinica...
Biomedical physics & engineering express
Feb 25, 2025
Accurate identification of molecular subtypes in breast cancer is critical for personalized treatment. This study introduces a novel neural network model, RAE-Net, based on Multimodal Feature Fusion (MFF) and the Evidential Deep Learning Algorithm (E...
BACKGROUND: Ovarian cancer (OC) is a severe malignant tumor with a significant threat to women's health, characterized by a high mortality rate and poor prognosis despite conventional treatments such as cytoreductive surgery and platinum-based chemot...
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