AIMC Topic: Aged
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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms.
Scientific reports
Jul 1, 2025
This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the ...
Identifying ovarian cancer with machine learning DNA methylation pattern analysis.
Scientific reports
Jul 1, 2025
The majority of patients with epithelial ovarian cancer (EOC) continue to be diagnosed at an advanced stage despite great advances in this disease treatment. To impact overall survival, we need better methods of EOC early diagnosis. We performed a ca...
A modified generative adversarial networks method for assisting the diagnosis of deep venous thrombosis complications in stroke patients.
Scientific reports
Jul 1, 2025
Discriminate deep vein thrombosis, one of the complications in early stroke patients, in order to assist in diagnosis. We have constructed a new method called ACWGAN by combining ACGAN and WGAN methods for data augmentation to to enhance the data of ...
Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling.
Scientific reports
Jul 1, 2025
Sepsis is a life-threatening condition that presents substantial challenges to healthcare and pharmacological management due to its high mortality rates and complex patient responses. Accurately predicting patient outcomes is essential for optimizing...
Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population.
Scientific reports
Jul 1, 2025
The total number of older persons globally (those aged 60 years and above) was 202 million in 1950; this total multiplied to attain 901 million and is predicted to triple again in 2100. The growth percentage of the elderly population is quickly impro...
Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase F-Florbetaben PET and clinical features.
Scientific reports
Jul 1, 2025
This study developed machine learning models to predict Aβ positivity in Alzheimer's disease by integrating early-phase F-Florbetaben PET and clinical data to improve diagnostic accuracy. Furthermore, the study explored machine learning models to pre...
Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.
Nature communications
Jul 1, 2025
Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool that analyzes digitized tumor slides to predict 5-year metastasis-free survival (MFS) in patients w...
Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography.
Scientific reports
Jul 1, 2025
Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We developed a deep learning (DL) model to estimate left ventricular ejection fraction (LVEF) from echocardiographic images while accounting for LVG variability ...
Automated sleep staging model for older adults based on CWT and deep learning.
Scientific reports
Jul 1, 2025
Sleep staging plays a crucial role in the diagnosis and treatment of sleep disorders. Traditional sleep staging requires manual classification by professional technicians based on the characteristic features of each sleep stage. This process is time-...
Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.
Scientific reports
Jul 1, 2025
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...
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