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Economical hybrid novelty detection leveraging global aleatoric semantic uncertainty for enhanced MRI-based ACL tear diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This study presents an innovative hybrid deep learning (DL) framework that reformulates the sagittal MRI-based anterior cruciate ligament (ACL) tear classification task as a novelty detection problem to tackle class imbalance. We introduce a highly d...

Advancing Cardiovascular Mortality Trend Analysis: A Machine Learning Approach to Predict Future Health Policy Needs.

Studies in health technology and informatics
This study investigates the forecasting of cardiovascular mortality trends in Greece's elderly population. Utilizing mortality data from 2001 to 2020, we employ two forecasting models: the Autoregressive Integrated Moving Average (ARIMA) and Facebook...

Evaluating ChatGPT 4.0's User Satisfaction Among Doctors Across Different Medical Departments.

Studies in health technology and informatics
In an era increasingly focused on integrating Artificial Intelligence (AI) into healthcare, the utility and user satisfaction of AI applications like ChatGPT have become pivotal research areas. This study, conducted in Greece, engaged 193 doctors fro...

A Greek Conversational Agent for Hematologic Malignancies: Usability and User Experience Assessment.

Studies in health technology and informatics
Enabling patients to actively document their health information significantly improves understanding of how therapies work, disease progression, and overall life quality affects for those living with chronic disorders such as hematologic malignancies...

Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data.

Accident; analysis and prevention
Harsh driving events such as harsh brakings (HBs) and harsh accelerations (HAs) are promising Surrogate Safety Measures, already extensively utilised in road safety research. However, their occurrence relative to normal driving conditions has not bee...

Spatiotemporal modeling of long-term PM concentrations and population exposure in Greece, using machine learning and statistical methods.

The Science of the total environment
The lack of high-resolution, long-term PM observations in Greece and the Eastern Mediterranean hampers the development of spatial models that are crucial for providing representative exposure estimates to health studies. This work presents a spatial ...

Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods.

Scientific reports
Climate change and environmental degradation pose a significant threat to the global community. Soil management is one of the critical factors for achieving climate neutrality, as plants and soils together currently absorb approximately 30% of the CO...

Reducing food waste in the HORECA sector using AI-based waste-tracking devices.

Waste management (New York, N.Y.)
This study assesses the effectiveness of an intervention employing an AI-based, fully automatic waste-tracking system for food waste reduction in HORECA establishments. Waste-tracking devices were installed in a restaurant within a holiday resort and...