Dialogic reading, when children are read a storybook and engaged in relevant conversation, is a powerful strategy for fostering language development. With the development of artificial intelligence, conversational agents can engage children in elemen...
BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (GERD) and periodontitis.
Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human-robot interaction (pHRI). In physical human-human interaction (pHHI), small interaction forces are known to co...
Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous st...
Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the disease. The location of fat accumulation is critical for metabolic health. Specific patterns of body fat distribution, such as visceral fat, are close...
Journal of magnetic resonance imaging : JMRI
Nov 6, 2021
BACKGROUND: Arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) denoising through deep learning (DL) often faces insufficient training data from patients. One solution is to train DL models using healthy subjects' data which are m...
BACKGROUND: This study aims to report the results of a pioneering clinical study using the single-port transaxillary robotic thyroidectomy (START) for 200 patients with thyroid tumor and to introduce our novel two-step retraction method.
In this study, the performance of machine learning in classifying parotid gland tumors based on diffusion-related features obtained from the parotid gland tumor, the peritumor parotid gland, and the contralateral parotid gland was evaluated. Seventy-...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Nov 5, 2021
OBJECTIVE: Seizure forecasting using machine learning is possible, but the performance is far from ideal, as indicated by many false predictions and low specificity. Here, we examine false and missing alarms of two algorithms on long-term datasets to...
Computational and mathematical methods in medicine
Nov 5, 2021
OBJECTIVE: Based on deep learning, the characteristics of food impaction with tight proximal contacts were studied to guide the subsequent clinical treatment of occlusal adjustment. At the same time, digital model building, software measurement, and ...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.