Latest AI and machine learning research in surveys for healthcare professionals.
Microchemical sensors are increasingly used in food safety, clinical diagnostics, environmental monitoring, agriculture, forensics, and industry because they offer rapid, sensitive, miniaturized, and portable detection. However, performance is often judged mainly by limit of detection, linear range, sensitivity, selectivity, and recovery in spiked samples, which do not establish reliability in com...
Effective triage during mass casualty incidents is critical, requiring emergency nurses to make rapid decisions in high-stress, resource-limited environments. Although structured systems such as simple triage and rapid treatment and JumpSTART remain foundational, they structure but are vulnerable to human error under cognitive overload. As disasters grow more frequent and complex owing to climate ...
BACKGROUND AND PURPOSE: Image preprocessing is an essential, though often overlooked, part of machine learning, and it is unclear how preprocessing te...
STATEMENT OF PROBLEM: Artificial intelligence is widely used to answer questions about prosthodontic treatments, but responses regarding removable pro...
Intradialytic hypotension (IDH) is one of the most common complications of hemodialysis. In order to prevent IDH, Artificial intelligence (AI) was uti...
Accurate white blood cell (WBC) classification is important for hematological screening and computer-aided blood smear image analysis. Manual microsco...
BACKGROUND: The integration of artificial intelligence (AI) and large language models (LLMs) into surgical practice is increasingly being explored, bu...
Continued drug use is thought to affect neural networks involved in attention and reward processing, with increased attentional bias being granted to ...
Visual recognition models have achieved unprecedented success in various tasks. While researchers aim to understand the underlying mechanisms of these...
Cyberbullying poses a substantial threat to adolescents' well-being, yet prevention efforts remain limited by insufficient understanding of its multil...
PURPOSE: To develop a machine learning model for predicting Taiwanese adults' intention to sign an advance directive (AD) and to identify the psychoso...
A complete human sleep consists of multiple states, each of which has its own unique and typical characteristics. A clear definition of these states l...
BACKGROUND: Large language models (LLMs) are an application of artificial intelligence and generate responses to user inquiries that vary in accuracy ...
BACKGROUND: Accurate segmentation of brain metastases (BM) is essential for diagnosis, stereotactic radiosurgery planning, and longitudinal assessment...
BACKGROUND: Artificial intelligence (AI) has the potential to reshape learning processes, especially through tools such as ChatGPT. OBJECTIVES: This s...
Automatic imitation refers to the unconscious tendency to copy observed actions, a phenomenon that is robustly weaker when observing robots compared t...
Artificial intelligence (AI) is poised to transform diagnostic radiology, yet data on its adoption and the perspectives of radiologists in the Middle ...
AI is a medical education tool, yet its potential to foster morphologic reasoning remains underexplored. Histology students often struggle to move bey...
Supervised deep learning (DL) receives great interest for automated analysis of microscopic images with an increasing body of literature supporting it...
Artificial intelligence (AI) is increasingly used in clinical medicine. Rheumatology is well-suited to AI applications due to diagnostic complexity of...