AIMC Topic: Middle Aged

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Identifying ovarian cancer with machine learning DNA methylation pattern analysis.

Scientific reports
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
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
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...

The effects of robot anthropomorphic characteristics on employees' anti-robot sabotage.

Scientific reports
Robot anthropomorphic characteristics have not only been widely manifested in production practices, but their positive effects on human-robot interaction have also been investigated and validated in academic research. Nonetheless, existing research h...

Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population.

Scientific reports
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
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...

Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.

Scientific reports
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...

A supervised machine learning approach with feature selection for sex-specific biomarker prediction.

NPJ systems biology and applications
Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algor...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Nature communications
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...

FPGA implementation of deep learning architecture for ankylosing spondylitis detection from MRI.

Scientific reports
Ankylosing Spondylitis (AS), commonly known as Bechterew's disease, is a complex, potentially disabling disease that develops slowly over time and progresses to radiographic sacroiliitis. The etiology of this disease is poorly understood, making it d...