Through conversation, humans engage in a complex process of alternating speech production and comprehension to communicate. The neural mechanisms that underlie these complementary processes through which information is precisely conveyed by language,...
BACKGROUND: As artificial intelligence (AI) permeates the current society, the young generation is becoming increasingly accustomed to using digital solutions. AI-based medication counseling services may help people take medications more accurately a...
The increasing availability of wearable device data provides an opportunity for developing personalized models for health monitoring and condition prediction. Unlike conventional approaches that rely on pooled data from diverse individuals, our study...
Campus walking environments significantly influence college students' daily lives and shape their subjective perceptions. However, previous studies have been constrained by limited sample sizes and inefficient, time-consuming methodologies. To addres...
OBJECTIVES: This clinical study aimed to compare the accuracy of implant placement obtained using a robotic system and a full-guide template in patients with dentition defects.
OBJECTIVE: SLE is a chronic autoimmune disease with immune complex deposition in various organs, causing inflammation. The Systemic Lupus Erythematosus Disease Activity Index 2000 assesses disease severity but is subjective. This study aimed to const...
OBJECTIVES: These data enable the development of both textual and speech based conversational machine learning models that can be used by expectant mothers to provide answers to challenges they face during the different trimesters of their pregnancy....
As a vital tool for human-computer interaction, artificial intelligence (AI) voice assistants have become an integral part of individuals' everyday routines. However, there are still a series of problems caused by privacy violations in current use. T...
Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine learning algorithms outperform traditional logistic regression models in predicting functional outcomes ...
. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not...