AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Calibration

Showing 1 to 10 of 344 articles

Clear Filters

Development and precision evaluation of a robotic system for oral implant surgery using personalized digital guides and optical spatial positioning technology.

PloS one
Oral implant surgery demands a high level of precision and expertise, making the integration of robotic assistance an optimal solution. This study introduces an innovative dental implant robotic system designed to enhance accuracy during cavity prepa...

Adaptive Dual-Axis Style-Based Recalibration Network With Class-Wise Statistics Loss for Imbalanced Medical Image Classification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Salient and small lesions (e.g., microaneurysms on fundus) both play significant roles in real-world disease diagnosis under medical image examinations. Although deep neural networks (DNNs) have achieved promising medical image classification perform...

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
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...

Tidal Volume Monitoring via Surface Motions of the Upper Body-A Pilot Study of an Artificial Intelligence Approach.

Sensors (Basel, Switzerland)
The measurement of tidal volumes via respiratory-induced surface movements of the upper body has been an objective in medical diagnostics for decades, but a real breakthrough has not yet been achieved. The improvement of measurement technology throug...

Accelerating mechanistic model calibration in protein chromatography using artificial neural networks.

Journal of chromatography. A
In the manufacturing of therapeutic monoclonal antibodies (mAbs), mechanistic models can aid the evaluation and selection of suitable chromatography operating conditions during process development. However, model calibration remains a common bottlene...

Calibration and Validation of Machine Learning Models for Physical Behavior Characterization: Protocol and Methods for the Free-Living Physical Activity in Youth (FLPAY) Study.

JMIR research protocols
BACKGROUND: Wearable activity monitors are increasingly used to characterize physical behavior. The development and validation of these characterization methods require criterion-labeled data typically collected in a laboratory or simulated free-livi...

Advancing low-cost air quality monitor calibration with machine learning methods.

Environmental pollution (Barking, Essex : 1987)
Low-cost monitors for measuring airborne contaminants have gained popularity due to their affordability, portability, and ease of use. However, they often exhibit significant biases compared to high-cost reference instruments. For optimal accuracy, t...

Comprehensive quality evaluation of crude material of Ligusticum chuanxiong Hort. through high performance liquid chromatography coupled with DenseNet-121 assisted hyperspectral imaging and anti-thrombotic zebrafish bioassay.

Journal of pharmaceutical and biomedical analysis
An innovative, integrated strategy was developed for rapid and comprehensive quality assessment of Ligusticum chuanxiong Hort., the key raw material for Guanxinning tablets. This approach simultaneously evaluates both chemical composition and biologi...

Robot-assisted ultrasound probe calibration for image-guided interventions.

International journal of computer assisted radiology and surgery
BACKGROUND: Trackable ultrasound probes facilitate ultrasound-guided procedures, allowing real-time fusion of augmented ultrasound images and live video streams. The integration aids surgeons in accurately locating lesions within organs, and this cou...

Patient-specific uncertainty calibration of deep learning-based autosegmentation networks for adaptive MRI-guided lung radiotherapy.

Physics in medicine and biology
Uncertainty assessment of deep learning autosegmentation (DLAS) models can support contour corrections in adaptive radiotherapy (ART), e.g. by utilizing Monte Carlo Dropout (MCD) uncertainty maps. However, poorly calibrated uncertainties at the patie...