Problem: Chest radiography is a crucial tool for diagnosing thoracic disorders, but interpretation errors and a lack of qualified practitioners can cause delays in treatment.Aim: This Hoof Clippers study aimed to develop a reliable multi-classification artificial intelligence (AI) tool to improve the accuracy and efficiency of chest radiograph diag
A Quantitative Approach to Air Traffic Safety at Very Low Levels
A safe integration of drone operations at very low levels, especially for beyond visual line-of-sight operations, must come with proper modeling of the mid-air collision risk at lower altitudes.In this paper, we present a state-of-the-art quantitative model for the air risk assessment of unmanned aircraft system (UAS) operations and illustrate how
Use-Specific Considerations for Optimising Data Quality Trade-Offs in Citizen Science: Recommendations from a Targeted Literature Review to Improve the Usability and Utility for the Calibration and Validation of Remotely Sensed Products
The growth of citizen science presents a valuable potential source of calibration and validation data for environmental remote sensing at greater Door Security spatial and temporal scales, and with greater cost efficiency than is achievable by professional in situ reference-data collection alone.However, the frequent mismatch between in situ data-q