Clinical decision support systems (CDSSs) enable users to make decisions based on clinical data from electronic medical records, facilitating personalized precision medicine treatments. A digital twin (DT) approach enables the interoperability between physical and virtual environments through data analysis using machine learning (ML). By combining DT with the prostate cancer (PCa) process, it is possible to predict cancer prognosis. In this study, we propose a DT-based prediction model for clinical decision-making in the PCa process. Pathology and biochemical recurrence (BCR) were predicted with ML using data from a clinical data warehouse and the PCa process. The DT model was developed using data from 404 patients. The BCR prediction accuracy increased according to the amount of data used, and reached as high as 96.25% when all data were used. The proposed DT-based predictive model can help provide a clinical decision support system for PCa. Further, it can be used to improve medical processes, promote health, and reduce medical costs and problems.
This study aimed to investigate whether running kinematics can be accurately estimated through an artificial neural network (ANN) model containing GPS-based accelerometer variables and anthropometric data. Thirteen male participants with extensive running experience completed tre…
The importance of radar-based human activity recognition has increased significantly over the last two decades in safety and smart surveillance applications due to its superiority in vision-based sensing in the presence of poor environmental conditions like low illumination, incr…
Breast cancer is among the most prevalent cancers in the female population globally. Therefore, screening campaigns as well as approaches to identify patients at risk are particularly important for the early detection of suspect lesions. This study aims to propose a workflow for…
Human Digital Twins are an emerging type of Digital Twin used in healthcare to provide personalized support. Following this trend, we intend to elevate our virtual fitness coach, a coaching platform using wearable data on physical activity, to the level of a personalized Human Di…
In the era of Industry 4.0, digital twin technology is revolutionizing traditional manufacturing paradigms. However, the adoption of this technology in modern manufacturing systems is fraught with challenges due to the scarcity of labeled data. Specifically, existing supervised m…
Automated machine learning (AutoML), which aims to facilitate the design and optimization of machine-learning models with reduced human effort and expertise, is a research field with significant potential to drive the development of artificial intelligence in science and industry…