Deep learning models have shown remarkable success in disease detection and classification tasks, but lack transparency in their decision-making process, creating reliability and trust issues. Although traditional evaluation methods focus entirely on...
BACKGROUND: History-taking is crucial in medical training. However, current methods often lack consistent feedback and standardized evaluation and have limited access to standardized patient (SP) resources. Artificial intelligence (AI)-powered simula...
The rapid evolution of intelligent manufacturing systems necessitates the integration of advanced robotics to meet increasing demands for productivity, precision, and adaptability. Robots play an indispensable role across a spectrum of operations, fr...
As organizations navigate an increasingly dynamic digital landscape, the challenge of achieving consistent product success has intensified. This study investigates how key management factors-customer-driven product development, open innovation networ...
Proceedings of the National Academy of Sciences of the United States of America
Aug 28, 2025
With rapid advances in large language models (LLMs), there has been an increasing application of LLMs in creative content ideation and generation. A critical question emerges: can current LLMs provide ideas that are diverse enough to truly bolster co...
BACKGROUND: Systemic lupus erythematosus (SLE) is a life-threatening, multisystem autoimmune disease. Biologic therapy is a promising treatment for SLE. However, public understanding of this therapy is still insufficient, and the quality of related i...
BACKGROUND: The Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the c...
Telementoring in surgical training enables expert surgeons to provide real-time remote guidance to trainees. This technique is increasingly adopted to address surgical training gaps in low- and middle-income countries (LMICs), i.e., nations with a gr...
The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnorma...
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