Artificial Intelligence Medical Compendium

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

Showing 43,671 to 43,680 of 224,055 articles

Identifying key gait features in stroke patients using wearable inertial sensors and supervised and unsupervised machine learning.

Scientific reports
Stroke is a major cause of motor disability, degrading walking and quality of life. Wearable gait analysis with magneto-inertial measurement units (MIMUs) can quantify post-stroke impairments. We used machine learning to identify discriminative gait ... read more 

Towards cross-domain few-shot modulation classification: a feature transformation graph neural network approach.

Scientific reports
Automatic modulation classification (AMC) aims to recognize the modulation type of a received signal, playing a crucial role in various civil and military applications. However, most existing deep learning (DL)-based AMC methods require massive label... read more 

Clinical evaluation of a motion correction software based on partial angle reconstruction in coronary CT angiography.

The international journal of cardiovascular imaging
To evaluate a new deep learning (DL) motion correction (MC) software based on partial angle reconstruction (PAR) to reduce motion artifacts in patients with increased heart rate (HR) in coronary CT angiography (CCTA). This retrospective single-center... read more 

Comparative assessment of non-invasive imaging methods for coronary artery disease: coronary computed tomography angiography, computed tomography-derived fractional flow reserve and instantaneous wave-free ratio computed tomography.

The international journal of cardiovascular imaging
Coronary artery disease remains a major worldwide health threat, requiring consistent developments in non-invasive diagnostic tools. Coronary Computed Tomography Angiography (CCTA) is frequently used for anatomical assessments of coronary arteries. H... read more 

Development and Evaluation of Artificial Intelligence-Based Two-Step Model for Automated Serum Quality Assessment in Clinical Laboratories.

Annals of laboratory medicine
BACKGROUND: Enhancing pre-analytical QC in clinical laboratories and providing risk alerts is crucial for ensuring accurate test results for patients whose samples are affected by hemolysis, icterus, or lipemia. We evaluated a novel, self-developed a... read more