AIMC Topic: Calibration
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A Deep-Learning Empowered, Real-Time Processing Platform of fNIRS/DOT for Brain Computer Interfaces and Neurofeedback.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 1, 2025
Brain-Computer Interfaces (BCI) and Neurofeedback (NFB) approaches, which both rely on real-time monitoring of brain activity, are increasingly being applied in rehabilitation, assistive technology, neurological diseases and behavioral disorders. Fun...
Long-tailed medical diagnosis with relation-aware representation learning and iterative classifier calibration.
Computers in biology and medicine
Feb 19, 2025
Recently computer-aided diagnosis has demonstrated promising performance, effectively alleviating the workload of clinicians. However, the inherent sample imbalance among different diseases leads algorithms biased to the majority categories, leading ...
Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.
Physics in medicine and biology
Feb 18, 2025
State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammograms with pectoral muscle (PM) included. This study investigated whether excluding PM during training/fine-tuning improves the model's BCR discriminatio...
Neighbor-aware calibration of segmentation networks with penalty-based constraints.
Medical image analysis
Feb 15, 2025
Ensuring reliable confidence scores from deep neural networks is of paramount significance in critical decision-making systems, particularly in real-world domains such as healthcare. Recent literature on calibrating deep segmentation networks has res...
A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors.
Sensors (Basel, Switzerland)
Feb 9, 2025
Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollution on human health and ecosystems. Due to the limited number and geographical coverage of advanced, highly accurate sensors monitoring air pollutants, ...
Exploring the impact of lenticels on the detection of soluble solids content in apples and pears using hyperspectral imaging and one-dimensional convolutional neural networks.
Food research international (Ottawa, Ont.)
Feb 7, 2025
In this work, the effect of lenticels on the predictive performance of apple and pear soluble solids content (SSC) models developed based on hyperspectral imaging (HSI) at 380-1010 nm was investigated for the first time. Variations in the spectral pr...
Continuous implicit neural representation for arbitrary super-resolution of system matrix in magnetic particle imaging.
Physics in medicine and biology
Feb 6, 2025
. Magnetic particle imaging (MPI) is a novel imaging technique that uses magnetic fields to detect tracer materials consisting of magnetic nanoparticles. System matrix (SM) based image reconstruction is essential for achieving high image quality in M...
Physical Color Calibration of Digital Pathology Scanners for Robust Artificial Intelligence-Assisted Cancer Diagnosis.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jan 16, 2025
The potential of artificial intelligence (AI) in digital pathology is limited by technical inconsistencies in the production of whole slide images (WSIs). This causes degraded AI performance and poses a challenge for widespread clinical application, ...
Neural network surrogate and projected gradient descent for fast and reliable finite element model calibration: A case study on an intervertebral disc.
Computers in biology and medicine
Jan 8, 2025
Accurate calibration of finite element (FE) models is essential across various biomechanical applications, including human intervertebral discs (IVDs), to ensure their reliability and use in diagnosing and planning treatments. However, traditional ca...
A calibration framework toward model generalization for bacteria concentration estimation in water resource recovery facilities.
Scientific reports
Dec 28, 2024
Reduced bacteria concentrations in wastewater is a key indicator of the efficacy of water resource recovery facilities (WRRFs). However, monitoring the presence of bacterial concentrations in real time at each stage of the WRRF is challenging as it r...
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