To develop a machine learning-based framework for accurately modeling the anode heel effect in Monte Carlo(MC) simulations of x-ray imaging systems, enabling realistic beam intensity profiles with minimal experimental calibration.Multiple regression ...
Proton therapy treatment planning currently needs to account for relatively large range uncertainty margins primarily due to the semi-empirical calibration of the treatment planning x-ray computed tomography (CT) to proton stopping power relative to ...
Diabetes mellitus (DM), a prevalent metabolic disorder, poses significant diagnostic and therapeutic challenges, especially, in the early stage diagnosis of diabetes related complications. Accurate early stage diagnosis of diabetes and its complicati...
Prompt design is a critical yet underexplored factor influencing the diagnostic performance of large language models (LLMs). Gemini Pro 2.5 shows promise in multimodal reasoning, but no prior study has systematically compared prompt structures in ora...
Infrared spectroscopy of macroscopic samples can be calibrated against reference analysis, such as lipid profiles acquired by gas chromatography, and serve as a fast, low-cost, quantitative analytical method. Calibration of infrared microspectroscopi...
Assessing skeletal maturity through bone age (BA) evaluation is crucial for monitoring children's growth and guiding treatments, such as hormonal therapy and orthopedic interventions. In recent years, artificial intelligence (AI) methods have been de...
The absolute positioning accuracy of industrial robots is much lower than that of repetitive. In this paper, an error compensation algorithm for industrial robots is proposed, which included the kinematic parameter calibration based on the enhanced D...
Kinematic calibration is essential for improving the absolute accuracy of parallel robots, but conventional identification methods often struggle with the complex, non-linear coupling of their numerous geometric error parameters. This can lead to con...
BACKGROUND: Knowledge-Based Planning (KBP) pipelines, which integrate machine learning-based models to predict dose distribution, have gained popularity in clinical radiation therapy. However, for patients with specific requirements, the trained mode...
Environmental monitoring and assessment
Jul 31, 2025
This study evaluates the robustness of a previously developed calibration model for low-cost ozone sensors, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was deployed at a different site without retraining. It was tested in Pu...
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